Reader reviews

Disappointing. The description oversold what is actually inside.

I read this over a couple of weekends alongside a small side project, which turned out to be the ideal way to approach it. Some of the material is available elsewhere, but rarely presented this clearly. The chapters on game development are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. Not one I will be returning to. There are better introductions to game development available.

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.

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.

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.

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

This is the third book I have read on ai & machine learning this year, and it is comfortably the best of them. The balance between theory and practice is well judged; neither side dominates. I found myself making notes in the margins, which is always a good sign. Three stars feels about right. It will stay on my shelf, but it will not be the first one I reach for.

Finally, a book that treats ai & machine learning with the care it deserves.

There is a particular kind of technical book that is dense without being difficult, and this is one of them. The explanations are careful without being condescending, which is a difficult balance to strike. A few of the examples could be more realistic, but the underlying points come across clearly. I appreciated the honesty about what the book does not cover — it saved me from expecting things that were not there. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.