If you want to learn Machine Learning but you’re worried you don’t have the math or the software background to master it, or you don’t know where to begin, this blog could be “one-stop shopping” for you: (it’s written in Google Colaboratory):

Why did I write this humorous, comprehensive blog? Because I have been where you are now. As a Humanities major (who once worked for “Saturday Night Live”), I suffered through two years of hell as I taught myself ML with online courses and blogs, and it was like drinking from a fire hose–too much information from too many experts with too many conflicting approaches, and my head was filled with confusion and self-doubt. Could I really learn this stuff?

IMO, today’s AI books and online courses suffer from “Expert Blindness.” Most of the experts have been experts for so long, and so deeply, that they forgot how a beginner sees the material. My blog skips no steps as I use analogies, pictures, examples and humor to break the concepts down into bite-size, user-friendly pieces, with minimal expert blindness. And every phrase has been double-checked by my mentor, who is a Stanford PhD in aerospace engineering.

It would make me happy to know I helped other folks to avoid the hell I went through. Please pass this blog on to any ML rookies, and I welcome all constructive comments to improve this as a resource for all future ML engineers!

Warmly,

David Code (yes, that really is my last name–what are the odds, right? 🙂