Meta-Guide to Mathematical foundations of ML

This is a guide of guides of what's available over the internet. Machine Learning might not be as hard as we once thought..
This list curates somewhat less popular resources on the internet, with a focus on the math background. There are so many other videos, MOCCs that are good and accessible. Chris Olah's blog is still my favourite so far

Conceptual Understanding

What we want to acheive:
Learning = Representation + Optimzation
Manifold and Topology
KL Divergence

Information Theory

Probability and Info T. from Deep Learning Book
Reddit ftw


Calculus on Backpropagation
Calculus on CNN (credits to Anthony)
Complicated RNN/LSTM

Research Direction

From OpenAI

If you have more to recommend, please let me know!

cover photo from OpenAi