STANFORD FORM (Responses)
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1
TimestampFirst name
Last name
Email
Codalab username
Affiliation/University
Preferences -- the hackathon track
Python knowledge (we will allocate people into groups with similar experience)
Starting filling the form -- checklist (you need to agree to all)
"Free lunch" compulsory check list (required homework)
Time taken --- ONE NUMBER in MINUTES
Registration checklist (confirm all)
Comments regarding the instructions (or the form in general)
Final standings
Country
3
11/07/2015 21:29:47EmanueleFumeo
emanuele.fumeo@edu.unige.it
efumeo
University of Genoa
Normal: Learn to make submissions with Python
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
100
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
I do not have any suggestion about these instructions, because I think they have been easy to follow and showed an appropriate level of detail.
It could have been useful to have a PDF version of the instructions (if any, I could not find them) in order to follow them before filling the information in this form, since I had to fill it again after closing my web browser to run the python script.
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
4
16/07/2015 00:54:05NimitaKulkarni
nakulkar@usc.edu
knimita
University Of Southern California
I will not attend the hackathon and the Free lunch -- only the lectures (8:45am..12am) , so I do not need to do the homework.
Beginner -- I never programmed in Python (I will learn at least the Python syntax by myself before the event)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
9999
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
Hi,

Participants who are not going to do homework (attending only lecture) can not answer - 'Time taken --- ONE NUMBER in MINUTES *'.

Thanks!
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
5
16/07/2015 01:01:55AkshitaRaina
akshitar@usc.edu
akshitaraina
University Of Southern California
I will not attend the hackathon and the Free lunch -- only the lectures (8:45am..12am) , so I do not need to do the homework.
Beginner -- I never programmed in Python (I will learn at least the Python syntax by myself before the event)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays
99999
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
6
16/07/2015 03:57:57PaulWatta
nothingpaul@yahoo.com
jumpseven
UM-Dearborn
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
60
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
7
16/07/2015 04:26:47paulalauren
palaure2@oakland.edu
SemanticPrincess
Oakland University
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
50
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
8
17/07/2015 23:04:50Vitaly
Lavrukhin
vitaly.lavrukhin@yahoo.com
V9
Samsung R&D Institute Rus
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
62
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
Russia
9
17/07/2015 23:34:39MehrdadYazdani
myazdani@gmail.com
myazdaniUCSD
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
30
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
US, California
10
19/07/2015 20:47:51
MaheshGoud
Tandarpally
mahesh2591@gmail.com
MaheshGoud
USC
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
180
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
I was running code on server where I don't have admin rights. So putting out command for pip local install yaml package might help others without admin rights to run code
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
US, California
11
20/07/2015 11:35:01NguyenDo
ndo@mednet.ucla.edu
back4good
UCLA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
65
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
US, California
12
20/07/2015 12:21:20SauravBiswas
sauravmaximus@gmail.com
sauravmaximus
Technical University of Kaiserslautern
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
100
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
Germany
13
20/07/2015 13:21:42AlexRyan
alexander.j.ryan@gmail.com
alexryanNA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
60
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
CA
14
20/07/2015 13:39:22AlexRyan
alexander.j.ryan@gmail.com
alexryanNA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
60
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
CA
15
20/07/2015 16:02:12paulalauren
palaure2@oakland.edu
SemanticPrincess
Oakland University
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
50
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
For some reason I got an email stating that I didn't register when I did a few days ago. Would recommend that registrant receive a confirmation email after submitting registration form.
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
USA
16
20/07/2015 16:07:07PaulaLauren
palaure2@oakland.edu
SemanticPrincess
Oakland University
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
50
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
sorry about resending but please use this form for my registration I don't think I selected the GPU/Deep Learning track on my last form and that's what I'd like to attend. Thanks.
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
USA
17
20/07/2015 16:09:53paulwatta
nothingpaul@yahoo.com
jumpseven
UM-Dearborn
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
65
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
USA
18
20/07/2015 16:26:26PeterLuh
pluh88@gmail.com
pluh889NA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
90
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
US, California
19
20/07/2015 16:42:14PeterLuh
pluh88@gmail.com
pluh889NA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
90
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
20
20/07/2015 17:35:22PeterLuh
pluh88@gmail.com
pluh889NA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
90
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
21
20/07/2015 20:02:11WalterMurphy
walter.murphy@gmail.com
wwwmurphy
NA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
70
1. I confirm the the time above is given in minutes, not hours or other unit, 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
22
20/07/2015 20:52:39MichaelYoung
mikalisk@gmail.com
meyouNA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
36
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, CA
23
20/07/2015 21:58:44Michael
D'Amour
mike@damourventures.com
mikedamour
NA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
70
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
US, California
24
21/07/2015 00:23:36Majid
Alkaee Taleghan
alkaee@gmail.com
alkaee
Oregon State University
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
180
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
FYI: I submitted my results on 07/20/2015 on 12:04:31, but the status is still running. Then, I resubmitted the same zip file gain.
I ran the homework on my desktop machine, but I will make sure to run it on my laptop too!
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, OR
25
21/07/2015 01:12:49franksharp
sharp.frank@gmail.com
drsharpNA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
80
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
usa
26
21/07/2015 01:24:16ThuyVu
vuthuyfo@gmail.com
vuthuyfoUCLA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
36
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
27
21/07/2015 02:45:58GuillermoAlvarez
stanmlbootcamp.frijas@xoxy.net
bodomoNA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
220
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
REQUEST: can we please use datasets that run well on, say, 3 GB RAM? Many laptops have only 4 GB RAM and it's tough to reduce the footprint of the OS, services, etc to much less than 1 GB. We're not going to learn anything more from datasets that require a couple GB more RAM, anyway.
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
28
21/07/2015 03:13:50ArthurPesah
arthur.pesah@gmail.com
artix41NA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
120
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
France
29
21/07/2015 06:33:01EmadAndrews
emad_andrews@yahoo.com
eandrews
Lead Data Scientist / IIROC
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
65
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
Canada
30
21/07/2015 08:05:37David
Lundgren
david.m.lundgren@gmail.com
maxlikelyRdio
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
40
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
California
31
21/07/2015 18:14:44SriKanajan
kanajan.sri@gmail.com
skanajanNA
Normal: Learn to make submissions with Python
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
225
1. I confirm the the time above is given in minutes, not hours or other unit, 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
the instructions here are not precisely in sync with the instructions on https://www.codalab.org/competitions/2321#learn_the_details-instructions

In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
CA
32
21/07/2015 19:37:31Vijay
Janakiraman
vijaymanikandaa@gmail.com
vijaymanikandan
NA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
95
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
33
21/07/2015 19:59:29Stanislaw
Jastrzebski
staszek.jastrzebski@gmail.com
kudkudak
Jagiellonian University
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
60
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
34
22/07/2015 17:58:55Ali
Chehrehsaz
Ali.chehrehsaz@gmail.com
achehrehsaz
NA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
2
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
California,U.S.
35
23/07/2015 01:35:09GeoffreyGamble
geoffreygamble@gmail.com
ggambleUCSD
Normal: Learn to make submissions with Python
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 and 2 from http://codalab.org/AutoML (1)., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
120
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1.
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
CA
36
26/07/2015 01:33:22KaranChugh
karanc06@gmail.com
karancNA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
90
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
37
26/07/2015 11:41:14Pradeep
Nagaraju
pradipbn@gmail.com
pradeepbnNA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
125
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
I know that there is a mention of 64bit OS. But please add it to the mandatory checklist.
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
38
26/07/2015 13:18:02Vitaly
Lavrukhin
vitaly.lavrukhin@yahoo.com
V9
Samsung R&D Institute Rus
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
62
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
Russia
39
27/07/2015 10:29:05YuantaoFan
fanyuantao@gmail.com
Yuantao
Halmstad University
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
60
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
Sweden
40
29/07/2015 14:12:33YaraRizk
yar01@aub.edu.lb
yar01
American University of Beirut
I will not attend the hackathon and the Free lunch -- only the lectures (8:45am..12am) , so I do not need to do the homework.
Beginner -- I never programmed in Python (I will learn at least the Python syntax by myself before the event)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
120
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
Even after following the above instructions, I was unable to reduce the run time to <400 on a 64bit intel i7 machine with 8GB RAM. Run time as approximately 700.
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
Lebanon
41
29/07/2015 19:02:45VinayRavuri
vravuri@qti.qualcomm.com
ravuriQualcomm
I will not attend the hackathon and the Free lunch -- only the lectures (8:45am..12am) , so I do not need to do the homework.
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
1
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
USA
42
29/07/2015 19:03:29VinayRavuri
vravuri@qti.qualcomm.com
ravuriQualcomm
I will not attend the hackathon and the Free lunch -- only the lectures (8:45am..12am) , so I do not need to do the homework.
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
1
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
USA
43
29/07/2015 19:03:35VinayRavuri
vravuri@qti.qualcomm.com
ravuriQualcomm
I will not attend the hackathon and the Free lunch -- only the lectures (8:45am..12am) , so I do not need to do the homework.
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
1
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
USA
44
29/07/2015 23:20:42FrancisCleary
francis@tivix.com
francisNA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
500
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, Oregon
45
30/07/2015 20:03:20PhilippRobbel
robbel@mit.edu
phitasticMIT
I will not attend the hackathon and the Free lunch -- only the lectures (8:45am..12am) , so I do not need to do the homework.
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl.
1
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems)
US, California
46
30/07/2015 20:11:45JannePeltola
janne.j.peltola@gmail.com
janne.peltola
Supercell
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
41
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
It took a pretty long time for CodaLab to ingest my submission. It only took me ~20 minutes to get things set up and to submit the ZIP file - the rest was just thumb-twiddling.
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
47
01/08/2015 16:59:34aurotripathy
auro@shatterline.com
auro@shatterline.com
IIT
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
1
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
48
01/08/2015 17:00:17aurotripathy
auro@shatterline.com
auro@shatterline.com
IIT
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
1
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
49
02/08/2015 01:58:22Johny RufusJohn
johnyrufus@gmail.com
rufus16Cloudera
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
92
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
United States
50
02/08/2015 18:06:48aurotripathy
auro@shatterline.com
AuroTripathy
IIT
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
1
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US
51
03/08/2015 01:27:25
Chandrashekar
Konda
Chandrak1907@gmail.com
Chandrak1907@gmail.com
USFCA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
40
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, CA
52
03/08/2015 01:35:17
Chandrashekar
Konda
chandrak1907@gmail.com
chandrak1907
USFCA
Normal: Learn to make submissions with Python
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
18
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
53
03/08/2015 03:01:17YoshiSakai
yoshi.sakai@gmail.com
bluemooninc
NA
I will not attend the hackathon and the Free lunch -- only the lectures (8:45am..12am) , so I do not need to do the homework.
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
1
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
Japan
54
03/08/2015 05:55:02stephaneegly
stephane.egly@gmail.com
nana
I will not attend at all -- I want to unregister
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form.
1. Register to Codalab at http://codalab.org.
1
1. I confirm the the time above is given in minutes, not hours or other unit
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news
us, california
55
03/08/2015 06:58:42Hussein
Al-barazanchi
hussein_albarazanchi@csu.fullerton.edu
hu_fulCSUF
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
57
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
56
03/08/2015 07:20:34Stanislaw
Jastrzebski
staszek.jastrzebski@gmail.com
kudkudak
Jagiellonian University
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
44
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
Poland
57
03/08/2015 08:55:20Florian
Unterkircher
fmu@fmu.name
fmuMatter
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
22
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
58
03/08/2015 16:12:37
mohammad
sanatkar
reza.sanatkar@duke.edu
reza_sanatkar
Duke University
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
120
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, North Carolina
59
03/08/2015 23:44:42Iroshani
Jayawardene
rjayawa@clemson.edu
iroshani
Clemson University
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Beginner -- I never programmed in Python (I will learn at least the Python syntax by myself before the event)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this)
60
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
I am using windows 8. Have a problem when running run.py. Get a numpy warning
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, South Carolina
60
04/08/2015 02:26:23YananJian
jianyanan@gmail.com
CharleneCMU
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
35
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
61
04/08/2015 21:11:01JulieLee
julie.lee@tubemogul.com
JulieTubeMogul, Inc.
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
30
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
62
06/08/2015 10:35:32DeepakAsrani
corp.dna@gmail.com
bdexpertSCU
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
45
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
63
06/08/2015 20:55:18Ashwini
Bhatkhande
ashwini.712@gmail.com
ash712UCLA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
60
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
64
07/08/2015 02:05:19Kirill
Igumenshchev
bribeme@gmail.com
kirilligumNA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
29
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
65
07/08/2015 02:17:09MitchellOwen
mitchell@udacity.com
mitchellowen
Udacity
Normal: Learn to make submissions with Python
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
82
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
66
07/08/2015 05:20:03TairiDelgado
tairi@udacity.com
tairiUdacity
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this)
120
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
USA
67
07/08/2015 05:20:03Arpan
Chakraborty
arpan.ncstate@gmail.com
arpanUdacity
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
120
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
68
07/08/2015 05:55:18Julie
Bernauer
jbernauer@nvidia.com
jbernauerNVIDIA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
1
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
Too much too read, too many instructions. No need for anaconda.
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
USA,CA
69
07/08/2015 11:38:24Peter
Kecskemethy
kecsky@gmail.com
kmasterOxford
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
241
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
UK
70
07/08/2015 16:23:44
Sanghamitra
Deb
sangha123@gmail.com
sangha123
NA
GPU: Participate in the GPU/deep learning group  (more interesting track -- knowledge of Python required)
Standard (basic knowledge of Python)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this), 13. Ensure that execution time (it is displayed on the leaderboard --> click 'Results') of your submission is low (a few seconds, usually should be around 1..4 seconds + a few seconds for possible delays, 14. If the execution time is still large (above 400.0) and there are predictions in the /res folder, check that the datasets are correct -- these should be datasets from Round 2 (at least, predictions for Round 1 can also be there). Datasets names of round 2 are e.g.:"albert", "dilbert"., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
20
1. I confirm the the time above is given in minutes, not hours or other unit, 2. If I chose the GPU track: Complete the reading prerequisites http://automl.chalearn.org/hackathon-icml/gpu-track-icml Chapter 2, point 1., 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
(OPTIONAL) Please add me to the NVIDIA mailing list for latest GPU news, In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
California
71
07/08/2015 19:38:11jaychen
c.c.owenchen@gmail.com
jaychenNTU
I will not attend the hackathon and the Free lunch -- only the lectures (8:45am..12am) , so I do not need to do the homework.
Beginner -- I never programmed in Python (I will learn at least the Python syntax by myself before the event)
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 10. Go in the directory [workdir] (one level up); retrieve the zip file generated automatically (5)., 11. Ensure that you ran successfully - submission (.zip) should have predictions for each of the 5 (or 10 if Round1 included) datasets in the /res folder. Of course the .zip should not contain the datasets!, 12. Submit the zip file to http://codalab.org/AutoML (6) (we will check this)
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1. I confirm the the time above is given in minutes, not hours or other unit
Only join lecture. Why Still need to confirm all checklist?
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
72
11/08/2015 00:39:15TsviAchler
achler@gmail.com
achlerNA
Normal: Learn to make submissions with Python
Advanced -- experience in programming (e.g. I work as software developer/ finish-(ed/ing) CS studies or equivalent, etc), good knowledge of Python.
1. I will measure (roughly == will be able to provide some indication) the overall time I spent for completing the homework and reading this form., 2. I will complete/confirm all the checkboxes related to this homework, before submitting the form, 3. I know the deadlines related to registration given on the hackathon webpage., 4. A computer to do the homework should have at least 8GB of RAM memory -- around 5GB of free memory is required. It should still be possible to run it if there are 4GB of RAM (even 64bit OS) using SWAP. Time budget is 20 minutes per dataset., 5. If my laptop has less than 6GB of memory, I will: a) restart the computer once I prepare code/datasets to run b) do not open any programs (especially a browser) while executing the code, to have more free memory, c) I will also close all not important programs which started on startup -- open a Task manager and sort programs by memory usage. Close all programs like Skype, GoogleDrive/Dropbox etc.
1. Register to Codalab at http://codalab.org., 2. Join the group https://groups.google.com/d/forum/automl., 3. Download all the datasets of round 1 (optional) and 2 (required) from http://codalab.org/AutoML (1). NOTE: you need to do predictions only on the datasets of Round 2 now, however, you will need also Round 1 during the hackathon., 4. Put all the data zip files [dataname].zip in a directory [datadir] and unzip them. The directory tree should look like [datadir]/[dataname]/[datafiles]., 5. Download and install Anaconda for Python 2.7 http://continuum.io/downloads (2)., 6. Download sample code from https://sites.google.com/a/chalearn.org/automl/hackathon-icml/sample_code_hackathon2_7.zip?attredirects=0&d=1, 7. Unzip the archive in a directory [workdir]/sample_code_hackathon/., 8. Edit run.py such that default_input_dir = [datadir] (3). DO NOT PUT DATA INSIDE THE FOLDER WITH CODE (sample_code_hackathon/), so the datasets are not included in the submission., 9. Run the code run.py from the directory sample_code_hackathon (4). NOTE: this should run about 1/4 of the total time budget, the total time budget is 200 minutes = 10 datasets * 20 minutes. All 10 datasets = round 1 and round 2 datasets. If you have a little of RAM memory (e.g. laptop with 2 GB of free memory), it might use SWAP memory and run too long. If my laptop has less than 6GB of memory, I will restart it now and do not open a browser/programs (as described above) while the code is running., 15. I confirm that the duration given in 'Duration' column on the leaderboard of my submission is below 400.0 -- else I will fix it now, BEFORE submitting this form (sorry that it is the same as above... -- this is important for the submission to be valid)
60
1. I confirm the the time above is given in minutes, not hours or other unit, 3. The registration will not be valid if my entry to the codalab platform (the homework above) together with the form will be not be submitted before August 7
received out of memory error
In case it will happen that I will not be able to attend the hackathon, I will inform the organisers about it (events@chalearn.org), Since the list of usernames, who will be registered to the hackathon, will be available on the hackathon webpage (after we process the registrations), I will be able to ensure whether my registration is definitely valid., I will bring a fully charged laptop to the hackathon event (on which I will work and on which I already tested that the sample code has run there without problems), Please do not ask us via email if you are accepted -- we will wait with verification till the end of July. We will post a list of participants (usernames) on the hackathon webpage.
US, California
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