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CS479: Machine Learning for 3D Data

Minhyuk Sung, KAIST, Fall 2023

Programming Assignments

Assignment 1 Due: September 17 (Sunday), 23:59 KST
Assignment 2 Due: October 9 (Monday), 23:59 KST
Assignment 3 Due: November 12 (Sunday), 23:59 KST
Where to submit: Gradescope

The last two assignments are optional. You are not required to submit your solutions for them. We kindly provide additional programming assignments to support you in gaining hands-on experience with well-established libraries.

Please carefully review the README of each assignment before you begin and check what you need to submit for each assignment.

Prerequisite

You'll need basic programming skills in PyTorch to complete the programming assignments. We do not provide tutorials on PyTorch, but there are plenty of resources available on the Internet.

The programming assignments are designed as a barometer to assess whether you are prepared for the course project. If you find the programming assignments too challenging, this course might not be the right fit for you.

Computing Resource

We have a limited number of GPUs available in KCLOUD. Only undergraduate students will be assigned one GPU.

KCLOUD Official Tutorial

KCLOUD X11 Forwarding Instructions

AI Coding Assistant Tool Policy

You are allowed (and even encouraged) to utilize AI coding assistant tools, such as ChatGPT, Copilot, Codex, and Code Intelligence, for your programming assignments and projects. Utilizing AI coding assistant tools will not be deemed as plagiarism. However, it is still strictly prohibited to directly copy code from the Internet or from someone else. Doing so will lead to a score of zero and a report to the university.

Grading

  • Check out the submission guidelines and grading policy of each assignment in the respective GitHub repository.
  • Late submission: A 20% penalty for each late day.