An absolute ground-up guide for data science, ml, and deep learning with python. A lot of this will start off overly basic, but will branch off to include model implementations and examples from Graduate ML/DL courses at MIT.
This is an effort to create an all-in-one QUICK guide to syntax and understanding models and how to apply them, as well as brush up on the bare minimum fundamentals for theory.