| layout | title | permalink |
|---|---|---|
default |
MATH 80600A - Machine Learning II<br>Deep Learning and Applications |
/project |
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 instruction can be found here (Eng & Fr).
The GCP tutorial can be found here (Eng).
-
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.
-
The suggested poster size is 36W x 48H inches or 90 x 122 cm. Some examples of posters in conferences are available here.
-
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.
-
You will be using Gather Town for your poster presentation.
-
We created a space here, and you will upload your project poster (in groups).
-
Here is a PDF tutorial and a 1-min video tutorial. The video might be outdated with an old Gather Town version, yet the high-level operations are the same.
TBA