I do not want in any way to sound critical and am genuinely curious about the dynamics of why people would find this interesting given it's reduced complexity.
Disclaimer: I'm such a developer! (currently going through the last bits of https://www.coursera.org/learn/machine-learning) - but I've noticed other around me recently.
The code is actually based on the original code from the book (e.g.: can be seen from the variable names like 'nabla') , but written in a more succinct manner. Since I am relatively new to Python, I found it easier to follow this repo's code than the code in the book and used it as my reference implementation.
It's missing quite a few things like calculating accuracy, regularization, etc. but they are quite straightforward to implement.
[1] Neural Networks and Deep Learning by Michael Nielsen - http://neuralnetworksanddeeplearning.com
At least, that's why i clicked the link.