Completing a course requires some serious dedication, and we are glad to see you made it. Here is a brief recap of the course.
We began with an introduction, followed by the programming model of JAX. Autograd and JIT are pretty cool.
Then we had a couple of chapters that offered a balance of theory and practice with JAX. This theory will be quite valuable for understanding some of the convoluted concepts in deep learning. For example, isn’t it cool to see a concept like Batch Normalization boiling down to just a two-line code (and a pretty neat theory) or how beautiful the theory behind Wasserstein GANs is.
Then we moved to the JAX ecosystem, a world of its own.
We’ll finish off the course by offering a summary of some excellent JAX-based libraries and models in the appendix to ensure you would be able to use this course as a launching pad for other problems. These lists are exhaustive and we’ll try to keep them updated, but you can always check the respective GitHub nevertheless.
Please share any feedback you have for us! We always appreciate it and hope to use your comments to make the next course even better.
We would like to sincerely thank you for taking the time to take this course. Also, we are grateful to all the team members involved throughout the life-cycle of course development and review. Finally, we are grateful to the JAX team for helping us by providing good documentation and their continuous support for a number of queries.
It was a great journey with you. We wish you the best of luck in your future endeavors with JAX and its libraries. Perpetuam Uitae Doctrina!!