FIRE SEMESTER 2: FIRE198-0112
Spring 2020
See our Post COVID-19 operations plan here.
Instructor: | Dr. Raymond Tu | Class Location: | ATL2339 |
Email: | hh2@umd.edu | Class Time: | Wed 2-2:50pm |
Office Location: | AVW3136 | Lab Location: | AVW3136 |
Office Hours: | See Lab hours | Lab Hours: | Mon 12-5pm, Tue-Fri 9am-5pm |
Peer Mentors: | Derek Zhang Jessica Qin Richard Gao Rung-Chuan (Joshua) Lo Siyuan Peng Vladimir Leung |
This course is the second in the sequence of three courses you will complete with the First-Year Innovation & Research Experience (FIRE) program. Through this course, you will be welcomed into your stream’s discipline, receive hands-on training in authentic research methods, and begin to take ownership of part of the stream’s research agenda as part of your development towards fearless career readiness.
Capital One Machine Learning is a research project-based class that spans over two semesters. This course will focus on the concepts related to the process of independent research, including collaboration with peers, communication of ideas, troubleshooting unexpected outcomes, and discipline-specific methodologies. Scheduled class meetings will focus on the discussion of primary literature, troubleshooting research issues, and continual review of individual and group research progress. Due to the unforeseen change in the FIRE research engagement, all students will be granted full credit for the in-lab research hours requirement. Research sessions in the lab will focus on training in current discipline-specific methods and practices, as well as giving students relevant experiences that seek to build resiliency and critical analysis skills.
At the completion of the course you will be able to:
All course materials will be posted to ELMS.
Please refer to the following website for all course policies:
http://www.ugst.umd.edu/courserelatedpolicies.html
A complete download is also available:
https://www.ugst.umd.edu/documents/CourseRelatedPolicies.pdf
As stated on this website:
The University expects each student to take full responsibility for their academic work and academic progress.
As a student you have the responsibility to be familiar with and uphold the Code of Academic Integrity and the Code of Conduct, as well as for notifying your course instructors in a timely fashion regarding academic accommodations related to absences and accessibility.
Student learning will be evaluated by 14 assessments (as further detailed in the Course Schedule). The course instructor will provide details on how each assessment will be evaluated for a final grade.
ASN | Description | % of grade |
1 | Setting Long-Term Goals & Self-Commitment | 2.5 |
2 | Testing MNIST Digits Classification with Real Handwriting | 5 |
3 | Testing CIFAR10 Image Classification with Real Photos | 5 |
4 | Testing CamVid Semantic Segmentation with Real Photos | 5 |
5 | Testing LFW Face Recognition Preprocessor with Real Photos | 5 |
6 | Testing LFW Face Recognition with Real Photos | 5 |
7 | Testing Open Images Object Detection with Real Photos | 10 |
8 | Team Contract | 2.5 |
9 | Fall Semester Project Preparation | 10 |
10 | Facial Recognition Team Project | 25 |
11 | Team Member Evaluation | 5 |
12 | Class Participation | 5 |
13 | Lab Attendance | 10 |
14 | FIRE Career Readiness | 5 |
Due to the unforeseen change in the FIRE research engagement, all students will be granted full credit for the in-lab research hours requirement.
Final Letter Grade Determination
This course uses plus and minus grading following the scale provided below. Final grades will be rounded to the nearest number. (Example: a final grade of 89.5 will be rounded up to 90. A final course grade of 89.4 will remain 89.4.)
Final letter grades will be determined using the following guidelines:
+ | 97.0% | + | 87.0% | + | 77.0% | + | 67.0% | ||
A | 93.0% | B | 83.0% | C | 73.0% | D | 63.0% | F | < 60.0% |
- | 90.0% | - | 80.0% | - | 70.0% | - | 60.0% |
This schedule is subject to change as the semester progresses.
Week | Prerequisite | Class Activity | Lab Activity | Assignment(s) |
1 | Intro to FIRE Capital One Machine Learning | Review learning materials & complete assignments | - Setting Long-Term Goals & Self-Commitment | |
2 | Install Packages for MNIST Digits Classification Project | MNIST Handwritten Digit Classification | Review learning materials & complete assignments | - Testing MNIST Digits Classification with Real Handwriting |
3 | Installing Packages for CIFAR10 Image Classification Project | CIFAR10 Image Classification | Review learning materials & complete assignments | - Testing CIFAR10 Image Classification with Real Photos |
4 | Installing Packages for CamVid Semantic Segmentation Project | CamVid Semantic Segmentation | Review learning materials & complete assignments | - Testing CamVid Semantic Segmentation with Real Photos |
5 | Installing Packages for LFW Face Recognition Project | LFW Face Recognition Preprocessor | Review learning materials & complete assignments | - Testing LFW Face Recognition Preprocessor with Real Photos |
6 | Installing Additional Packages for LFW Face Recognition Project | LFW Face Recognition | Review learning materials & complete assignments | - Testing LFW Face Recognition with Real Photos |
7 | Open Images Object Detection Preprocessor | Open Images Object Detection Prerequisite | Review learning materials & complete assignments | - Testing Open Images Object Detection with Real Photos - Class Participation I - Lab Attendance I |
8 3/16-3/20 | SPRING BREAK | |||
9 3/23-3/27 | EXTENDED CLOSURE | |||
10 3/30-4/3 | Open Images Object Detection | Review learning materials & complete assignments | - Team Contract | |
11 4/6- | Team formation | Intro to Facial Recognition Team Project Intro to COML Fall Semester Projects | Work on team project & assignments | - Fall Semester Project Prep: Dataset Review |
12 | Facial Recognition Team Project Review Fall Semester Projects Dataset/Paper/Code Review | Work on team project & assignments | - Team Member Evaluation I - Fall Semester Project Prep: Paper Review | |
13 | Facial Recognition Team Project Review Fall Semester Projects Dataset/Paper/Code Review | Work on team project & assignments | - Fall Semester Project Prep: Code Review | |
14 | FIRE Career Readiness FIRE Survey | Work on team project & assignments | - FIRE Career Readiness | |
15 | Facial Recognition Team Project Demo | Complete final assignments | - Team Member Evaluation II - Class Participation II - Lab Attendance II - Facial Recognition Team Project: Live Demo - Facial Recognition Team Project: Final Code | |
END OF COURSE |