Seeking advice on an ML tutorial for rookies without math or software background

I am the author of this 70-page, beginner-friendly intro to deep learning, and I seek your advice on how to improve it, please.

I wrote this humorous tutorial in an attempt to save other rookies some pain. I suffered through two years of teaching 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 gaps between concepts, and I was filled with confusion and self-doubt. Could I really learn this stuff? My head was so full of anxious chatter that it left little bandwidth to actually focus on learning the concepts.

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 forget how a beginner sees the material. My blog skips very few steps as I use analogies, pictures, examples and humor to break the concepts down into bite-size, user-friendly pieces, with minimal expert blindness.

It would make me happy to know I helped other folks to avoid some of the pain 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? :-)