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.<p>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.<p>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).<p>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