Code of Honor

This project is intended to deepen your understanding and develop your skills, and it forms a substantial part of your final evaluation. It must be completed collaboratively as a group. Any form of academic dishonesty is a violation of the Code of Honor. You are encouraged to use publicly available resources, provided that all sources are clearly cited and your individual contributions are clearly explained. Failure to properly acknowledge your contribution may be considered a lack of participation, and projects without meaningful individual contributions will be deemed incomplete.

The course project will be seriously started in the second half of the course. In these project, you choose a topic from the list of available topics and work through semester to deliver the requested outcomes of the project. Regardless of topic of the project, you will need to follow the following steps:

  1. Make a group of 3 or 4. Due to the course size, smaller group size is only accepted under special circumstances, e.g., working on an open-ended topic of your own or a group member dropping in the middle of semester.
  2. Submit your topic by the end of Week 5. It is strongly suggested to choose as soon as possible to get into the problem and start preliminaries.
  3. You will be allocated to a TA, who could help you throughout the project.
  4. Deliver initial milestones of the project in a progress briefing by Week 10. The progress briefing will serve as the base for your final report.
  5. Deliver your final results by the end of semester. This includes the final report, the source codes, and a final presentation in our internal seminar.

Submission Procedure

The main body of work is submitted through Git. In addition, each group submits a final paper and gives a presentation. In this respect, please follow these steps.
  • Each group must maintain a Git repository, e.g., GitHub or GitLab, for the project. By the time of final submission, the repository should have:
    • Well-documented codebase
    • Clear README.md with setup and usage instructions
    • A requirements.txt file listing all required packages or an environment.yaml file with a reproducible environment setup
    • Demo script or notebook showing sample input-output
    • If applicable, a /doc folder with extended documentation
  • A final report (maximum 5 pages) must be submitted in a PDF format. The report should be written in the provided formal style, including an abstract, introduction, method, experiments, results, and conclusion.
    Important: Please make sure to complete the section Consent for Information Sharing. Important: Submissions that do not use template are considered incomplete.
  • A 5-minute presentation (maximum 5 slides including the title slide) is given on the internal seminar on Week 15, i.e., Dec 8 to Dec 12, by the group. For presentation, any template can be used.

Project Topics

  • The project is in general open-ended and its topic can be anything related to Deep Learning
  • A list of suggested topics can be found on this Google Doc
  • If you choose from the list of topics, please add a comment to that topic indicating that you have taken this topic. This is only to follow the distribution of the topics
  • No need to select from the list. You are welcome and indeed encouraged to develop your own proposal.

Templates for Proposal, Report and Presentation