The Blunt Guide to Mathematically Rigorous Machine Learning

I recently wrote a brief guide on the Math required for Machine Learning. People liked it, and asked me to write one on how to master ML at a mathematically rigorous, conceptual level. That is the focus of this guide, no bullshit, no easy routes, and real, fundamental understanding. I'll be going through the later part of the curriculum myself. A quick question to ask yourself: Why do I want to learn ML?