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| title | MATH 80600A - Machine Learning II<br>Deep Learning and Applications |
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The goal of the course project is to apply deep learning techniques learned in class (it is fine if you use the techniques not introduced in class) to solve real-world problems or develop new deep learning techniques. You are expected to work in teams and learn to collaborate with your teammates. Each group should make a poster in the final class and participate in the poster session to present your results and communicate with other teams. A report should also be submitted at the end of the course.
Full instructions can be downloaded here. GCP tutorial can be found here.
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The project proposal is a summary of your proposed research topic and study plan. It should include the background of the problem (context and motivation), problem definition, and a plan on how you want to study it. The project proposal should be at most 2 pages.
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The suggested poster size will be updated later. Some examples of posters in conferences are available here.
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The final report should give a comprehensive description of your projects. It should contain a section about the motivation and definition of your selected topics, a section summarizing the related work, a section on the techniques you used for solving the problem, an empirical section presenting your data sets and results with detailed analysis, and a conclusion section. The report should be at most 8 pages (not including references) using the NeurIPS format. The final report should be submitted in pdf format.
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You will be using Gather Town for your poster presentation.
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We created a space here, and you will upload your project poster (in groups).
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Here is a PDF tutorial and a 1-min video tutorial.
- Proposal due: Feb. 28th
- Poster due:
- J1: Apr. 8th
- J2: Apr. 16th
- Final report due: Apr. 25th
- Note: 3 points will be deducted for late submission.
The groups for course projects can be found at the Google sheet for J1 and J2.