Reader reviews

Finally, a book that treats psychology with the care it deserves.

This is the third book I have read on psychology this year, and it is comfortably the best of them. The author is unusually honest about where the simplifications break down, which I appreciated. The progression from chapter to chapter is well thought out; nothing feels out of order. Some of the diagrams are dense and I had to reread a few sections, though that may just be me. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.

Better than I expected. Rare to find a technical book this well judged.

A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. A couple of chapters felt like they could have been merged, but that is a minor complaint. Some terminology is introduced without much ceremony; I had to look a few things up along the way. An easy five stars from me. I look forward to whatever the author writes next.

A worthwhile addition to my shelf, with realistic expectations.

I had been on the fence about this one for a while, and I should have bought it sooner. A couple of chapters felt like they could have been merged, but that is a minor complaint. The examples are small enough to type out and experiment with, which is exactly what I want from a book like this. The book rewards careful reading. Skimming it would be a mistake. Four stars, and I suspect a second edition could easily push it to five.

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 writing is direct and does not waste space on filler, which I value in a technical book. The exercises at the end of each chapter are worth doing — they caught a few misconceptions I did not know I had. Solid, and I would buy another book from this author without hesitation.

Solid and well-organised. A couple of chapters dragged a little.

I was looking for something that would bridge the gap between tutorials and proper reference material, and this does that well. The examples are small enough to type out and experiment with, which is exactly what I want from a book like this. I found myself making notes in the margins, which is always a good sign. A good addition to a technical library, as long as you know what you are buying.

The clearest explanation of ai & machine learning I have come across.

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 chapters on ai & machine learning are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. I found myself making notes in the margins, which is always a good sign. Worth the money and the reading time, without hesitation.