r/deeplearning - How can I understand the maths of back propagation of neural network, CNN and RNN?

I'm currently writing a series of blog posts aimed at demystifying the maths behind deep learning. I've gone through the intuition as well as step-by-step through the maths, and I've also got code samples for you to implement the neural networks from scratch. Hope you find the posts useful, please comment if there are parts that could be made clearer. I'll be posting the RNN/LSTM backprop posts in a few days, in the meantime I have already posted the CNN and neural network backprop posts if you want to check that out.