Hidden Gems on Basic ML Concepts [D]

I just rediscovered an article on visual information theory by Colah: [https://colah.github.io/posts/2015-09-Visual-Information/](https://colah.github.io/posts/2015-09-Visual-Information/)

I've used cross-entropy in different ML projects but never understood it fully. This article explained Entropy as a "continuous analog" of Shannon codes - which I thought offered a unique perspective on this basic concept.

What are some articles you find interesting?

analog article articles concept continuous cross-entropy entropy explained machinelearning ml projects perspective projects thought