[antpls]

Good reading ! It would be interesting to have other similar challenges, such as Euler, solved in idiomatic Tensorflow and Pytorch. Also some examples of more complicated state-of-the-art algorithms, such as sorting/graph/trees algorithms reimplemented in these frameworks.

It would be a great introduction to these frameworks for people who never touched anything ML-related, leaving the neural network content to later in the learning process.

Learning how to create differentiable algorithms and neural networks would be easier once the way those frameworks work is understood (ingesting data, iterating dataset, running, debugging, profiling, etc).

If you are starting with neural networks or differentiable programming, learning both the maths and the frameworks at the same time can be quite overwhelming