Reader reviews

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

There is a particular kind of technical book that is dense without being difficult, and this is one of them. There is a section near the end that ties several earlier ideas together in a way I had not seen before. The author is unusually honest about where the simplifications break down, which I appreciated. This is the book I wish had existed when I started working with ai & machine learning.

Some sections were excellent and others felt like filler.

I had been on the fence about this one for a while, and I should have bought it sooner. The author clearly knows the subject deeply and has thought hard about how to teach it. The index and cross-references are surprisingly good, which matters for a book I will come back to. The chapters on game development are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. Useful as a reference, less so as a straight read from cover to cover.

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.

Genuinely excellent — I finished it in a week and immediately started again.

A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. The code samples assume a particular environment, which took a bit of fiddling to get running properly. Some of the diagrams are dense and I had to reread a few sections, though that may just be me. This is the book I wish had existed when I started working with ai & machine learning.

An enjoyable and informative read, though it could have been shorter.

I was looking for something that would bridge the gap between tutorials and proper reference material, and this does that well. The author is unusually honest about where the simplifications break down, which I appreciated. The book rewards careful reading. Skimming it would be a mistake. Worth picking up if you already have the basics. Set realistic expectations and you will get a lot out of it.

A useful guide. The examples assume a particular environment, but that is fixable.

I had been on the fence about this one for a while, and I should have bought it sooner. The chapters on ai & machine learning are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. Some of the diagrams are dense and I had to reread a few sections, though that may just be me. A good addition to a technical library, as long as you know what you are buying.