Pull the latest commits from master branch before committing your code to your branch. When you finish working on your branch, submit a pull request so that someone else can review your code and test it.
In the repository, there is a environment.yml file that you can use to generate an Anaconda environment automatically. On Windows, you can import this in the Anaconda GUI. On Mac OS and in Linux, you can use the command conda create --name ece542projects --file=environment.yml.
Be sure to activate the environment when you are coding locallly in a jupyter notebook. In Anaconda, you can do this from the GUI when you open a jupyter notebook and use the environment as your IPython kernel for the notebook. On Mac OS and Linux, use the command conda activate ece542projects. Feel free to use this environment for your other projects. It should contain most of the libraries you need to work with ML.
We will use Github to keep track of our code and stay organized. On your machine, open up your own development branch using github checkout -b name-of-your-branch and commit to that branch while you are working on your task. You can upload your jupyter notebook to Google Drive and run it using Colab on there. When you finish, be sure to download it to your branch, commit your changes, and upload it to Github.