Assignment 1
Due Feb 9, 2021
Approximate Load: 3 hours
Goal: Ensuring “Code-not-running” issues are resolved ahead of time, and that students' systems are set-up to start coding and exploring potential projects. Students are only expected to install packages and test run them on their own systems.
Deliverables:
Depending upon your past experience with machine learning/deep learning, you can pick one of two tracks:
Track A (beginners): Assignment details are given here on the Github Repository
In summary, here are the steps:
Fork the github repo. (NOTE: do not clone it, please fork the repo.) Add your forked repo link to this google spreadsheet: Follow the instructions on the repo to Install Conda, PyTorch and other often used packages. Run given test code on your own system to ensure things run on your own system. Submit output of test code on canvas. NOTE: If you don't have GPU access yourself, you can explore google colab (Links to an external site.). If you do so, please do let us know so we are informed Track B (connoisseurs):
If you have sufficient experience with machine learning, and would like to not rely on the code base used by the rest of the class, all you need to do is provide us some evidence that you can run/write machine learning code yourself. Examples of this could include: 1) github repositories of past projects/code that you have written, 2) a report that you have written, code that you have run for another course, 3) Course contents/names of other relevant classes you have taken, 4) any other documents/codebases you might want to share. For any questions, feel free to reach out to the teaching staff via slack!
