Last name

Codalab username

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)

Final standings

emanuele.fumeo@edu.unige.it

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)

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)

nakulkar@usc.edu

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)

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)

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

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)

nothingpaul@yahoo.com

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)

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)

palaure2@oakland.edu

SemanticPrincess

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)

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)

Lavrukhin

vitaly.lavrukhin@yahoo.com

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)

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)

myazdani@gmail.com

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)

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)

MaheshGoud

Tandarpally

mahesh2591@gmail.com

MaheshGoud

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)

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)

ndo@mednet.ucla.edu

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)

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)

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)

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)

alexander.j.ryan@gmail.com

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)

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)

alexander.j.ryan@gmail.com

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)

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)

palaure2@oakland.edu

SemanticPrincess

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)

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.

palaure2@oakland.edu

SemanticPrincess

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)

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.

nothingpaul@yahoo.com

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)

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.

pluh88@gmail.com

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)

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)

pluh88@gmail.com

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)

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.

pluh88@gmail.com

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)

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.

walter.murphy@gmail.com

wwwmurphy

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)

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.

mikalisk@gmail.com

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)

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.

mike@damourventures.com

mikedamour

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)

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)

Alkaee Taleghan

alkaee@gmail.com

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)

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.

sharp.frank@gmail.com

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)

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.

vuthuyfo@gmail.com

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)

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.

stanmlbootcamp.frijas@xoxy.net

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)

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.

arthur.pesah@gmail.com

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)

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.

emad_andrews@yahoo.com

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)

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.

Lundgren

david.m.lundgren@gmail.com

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)

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.

kanajan.sri@gmail.com

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)

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.

Janakiraman

vijaymanikandaa@gmail.com

vijaymanikandan

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)

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.

Jastrzebski

staszek.jastrzebski@gmail.com

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)

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.

Chehrehsaz

Ali.chehrehsaz@gmail.com

achehrehsaz

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)

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.

geoffreygamble@gmail.com

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)

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.

karanc06@gmail.com

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. 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.

pradipbn@gmail.com

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. 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.

Lavrukhin

vitaly.lavrukhin@yahoo.com

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)

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.

fanyuantao@gmail.com

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. 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.

yar01@aub.edu.lb

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)

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.

vravuri@qti.qualcomm.com

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. 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.

vravuri@qti.qualcomm.com

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. 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.

vravuri@qti.qualcomm.com

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. 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.

francis@tivix.com

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. 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.

robbel@mit.edu

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. 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)

janne.j.peltola@gmail.com

janne.peltola

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. 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.

auro@shatterline.com

auro@shatterline.com

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. 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.

auro@shatterline.com

auro@shatterline.com

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. 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.

johnyrufus@gmail.com

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. 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.

auro@shatterline.com

AuroTripathy

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. 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.

Chandrashekar

Chandrak1907@gmail.com

Chandrak1907@gmail.com

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. 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.

Chandrashekar

chandrak1907@gmail.com

chandrak1907

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)

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.

yoshi.sakai@gmail.com

bluemooninc

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. 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.

stephane.egly@gmail.com

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. 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

Al-barazanchi

hussein_albarazanchi@csu.fullerton.edu

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. 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.

Jastrzebski

staszek.jastrzebski@gmail.com

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)

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.

Unterkircher

fmu@fmu.name

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. 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.

reza.sanatkar@duke.edu

reza_sanatkar

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. 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.

Jayawardene

rjayawa@clemson.edu

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)

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.

jianyanan@gmail.com

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. 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.

julie.lee@tubemogul.com

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. 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.

corp.dna@gmail.com

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)

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.

Bhatkhande

ashwini.712@gmail.com

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. 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.

Igumenshchev

bribeme@gmail.com

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. 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.

mitchell@udacity.com

mitchellowen

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)

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.

tairi@udacity.com

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)

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.

Chakraborty

arpan.ncstate@gmail.com

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. 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.

jbernauer@nvidia.com

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. 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.

Kecskemethy

kecsky@gmail.com

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. 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.

sangha123@gmail.com

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. 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.

c.c.owenchen@gmail.com

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)

1. I confirm the the time above is given in minutes, not hours or other unit

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.

achler@gmail.com

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)

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

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.