OPEN A BOOK. FIND A LITTLE JOY.

Useful in parts. Fine as a reference, less so as a cover-to-cover read.

I read this over a couple of weekends alongside a small side project, which turned out to be the ideal way to approach it. The exercises at the end of each chapter are worth doing — they caught a few misconceptions I did not know I had. I found myself making notes in the margins, which is always a good sign. Useful as a reference, less so as a straight read from cover to cover.

Excellent from start to finish. No filler, no padding.

This is the third book I have read on ai & machine learning this year, and it is comfortably the best of them. Some of the material is available elsewhere, but rarely presented this clearly. Some terminology is introduced without much ceremony; I had to look a few things up along the way. Worth the money and the reading time, without hesitation.

Exactly the book I needed. Straight to the point and genuinely useful.

I came to this book already familiar with the basics, and it still had plenty to offer. There is a section near the end that ties several earlier ideas together in a way I had not seen before. The explanations are careful without being condescending, which is a difficult balance to strike. The author is unusually honest about where the simplifications break down, which I appreciated. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.