Notes On Using
Python and Data Science
To Make Cool Stuff

For a good while, whenever I'd start to learn something new, I'd go down a rabbit hole of documentation, books, YouTube videos, etc. As I dug deeper and deeper into the material, I'd leave behind mountain of scratch paper where I'd jotted along. Then (if I even found the time) I'd rewrite/distill it into some Moleskine notebook for "easy reference" later.

Then, of course, you have to know how to reference all of your reference materials. If I forgot to bring my notebook to work, I'd be out of luck. Or better yet, how would I share the notes that I took if they might be useful for someone else?

So, by the time I found Chris Albon's excellent note-compiling repository it felt like the answer to all of my problems. After a good deal of reverse-engineering, this page is less about curating a body of work, and more a consistent place that I can stage the things I'm figuring out. That means that I don't intend to brain-dump all of the things I know just to fill space. If you're new and looking for beginner materials, this might prove more helpful!

Python

Object Oriented Programming

Machine Learning

Generative Adversarial Networks

Stats and Math

PySpark

Miscellaneous Algorithms

Markov Chains