Oh sure. I say the same to my students. But the particular spin on this book makes it look to non-experts that this is the math you need to do something useful

Oh sure. I say the same to my students. But the particular spin on this book makes it look to non-experts that this is the math you need to do something useful with deep learning. And that's just not true. Certainly you need to understand what you're optimizing, how your optimizer works, what your objective function is doing, etc. But the vast majority of people don't need to know about theoretical approximation results for problems that they will never actually encounter in real life, etc. For example, I have never used used anything like "6.1.3 Lyapunov-type stability for GD optimization" in a decade of ML research. I'm sure people do! But not on the kinds of problems I work on. Just look at the comments here. People are complaining about the lack of context, but this is fine for the audience the book is aimed at. It's just the average HN reader. I think it would be better if the authors chose a different title. As it stands, non-experts will be attracted and then be put off, and experts will think the book is likely to be too generic.