This is a fantastic list.<p>I've been trying to teach myself ML and AI for a while now, and though only tangentally relevant to the article perhaps others can take a few tips from my experience. First, I didn't really have a breakthrough until I ditched the 'recommended' textbooks and video courses and just started picking out a topic and learning by doing. Anything I don't understand or know when trying to implement it I just google/youtube/wikipedia it and keep messing with it until I know how it works at a conceptual level. Thats where resources like this article really come in handy.<p>For the heavier math parts, I just write a short summary of the formula and what its various parameters do and try to make a mental note of it. I certainly do not try to use the formulas to solve complex mathematical problems or write an implementation in python. I chalk this task up to `someday when I have the time`.<p>Finally, I'll get a dataset and try to solve various problems using the new skill I just learned using R/python & co.<p>Thats it.<p>This method has ridiculously accelerated the speed at which I've been able to acquire ML/AI skills that I also know how to apply in the real world. Before I felt like I was moving at a snails pace.<p>This method might not work well for everyone but its at least an interesting alternative to most of the recommendations of doing A,B,C online courses and reading X,Y,Z books.