Kaggle is the world’s largest data science community. One of Kaggle’s features is “Notebooks”, which is “a cloud computational environment that enables reproducible and collaborative analysis”. In particular, Kaggle provides access to GPUs for free. Every lesson provides direct links to notebooks on Kaggle that are ready for you to start using. Click “Copy & Edit” at the top right of any notebook to start working with it.

In order to use a GPU on Kaggle, your account must be phone verified. You can enable this on your account page (after you’ve signed up and are logged in) under “Phone Verification”.

Here’s some information from Kaggle’s notebook page:

Jupyter notebooks consist of a sequence of cells, where each cell is formatted in either Markdown (for writing text) or in a programming language of your choice (for writing code). To start a notebook, click on “Create Notebook”, and select “Notebook”. This will open the Notebooks editing interface.

Comprehensive data exploration with Python” is a great example of a Python Jupyter Notebook-type.

Instead of Kaggle, you can also use Paperspace Gradient. We’ve found they work really well for this course, and have good free options. If you don’t have a Paperspace account yet, sign up with this link to get $10 credit – and we get a credit too. Gradient is a little harder to use because the notebooks are not ready-to-run, but it’s more powerful because you get a full Linux environment to work in. It’s a good option for folks who are comfortable working with git and the command line. To access the course notebooks on Paperspace, you will need to clone this GitHub repo.