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.

Important Note on Overlap

Some students are taking this course along with ECE1508: Applied Deep Learning. Note that you cannot present the same project in both courses. Any overlap between the projects should be discussed in advance with the instructor.

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. 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.
  6. In case of conflict between team members regarding the project topic and specifics or tasks, it is expected that the group manage the conflict. Teaching team will not intervene to resolve conflicts.
  7. Use of AI: Responsible use of AI is allowed to enhance productivity. This means that you can use AI for brainstorming, deep research, debugging, or sanity check. Relaying on AI to decide for the design or build the main part of project, e.g. copying directly texts, modules, or a big chunk of code generated by AI, is not accepted. Any use of AI must be reported in the final report (see the AI Attestation part in the template).

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.
    • The repository must be initiated by the proposal submission deadline.
  • 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 must be written in the provided formal style, including an abstract, introduction, method, experiments, results, and conclusion.
    • Important: Please make sure to complete the sections Teamwork Attestation, Consent for Information Sharing, AI Attestation.
    • 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 second week of April, i.e., April 6 to Dec 10, 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 will be released. Nevertheless, there is no need to select from the list. You are welcome and indeed encouraged to develop your own proposal.

Some Advices and Suggestions

The following are guidelines that help you organize the project and meet expectations.

  • Use the Piazza post Find a project partner or other means to form a group of 3.
  • Reach out to your teammates to discuss the project topic.
  • Brainstorm ideas and use online libraries to define the scope of your project.
  • Gather results that validate your solution. You should decide on your own metrics to evaluate your own work.
  • Prepare the report in Project Report Template. The report must not exceed 5 pages excluding references and appendices. Do not use Microsoft Word.
  • The report should be technically sound, and not casually mention decisions without justifying them. Hiding some technical details is acceptable as details will be there in your source code. For example, the report should not mention that you used NumPy, but it should mention that you used stochastic gradient descent with a learning rate of 0.0001.
  • Write well. Presentation including quality of writing, figures and organization accounts for a significant part of your grade. If your grader doesn’t understand your writing, that will severely impact your grade.
  • We recommend documenting who did what to ensure if conflict arises there is enough evidence to resolve it.

Attention

In engineering and science, this is a common practice that one solution does not work or what you implement does not give the expected results. So, if your solution/implementation does not give any improvement, does not answer the problem you had initially, or does not return the same result as you expect from the literature, it's all OK! You can still submit your project and it will be marked taking all the items mentioned above. You should never by any means try to fake results or copy from online resources! An incomplete course project would never be worse than fake results or a copied project!

Templates for Proposal, Report and Presentation