Reader reviews

This is the one to get if you are serious about ai & machine learning.

There is a particular kind of technical book that is dense without being difficult, and this is one of them. The author avoids over-explaining, which keeps the pace up but means you need to pay attention. The early chapters move quickly through material I already knew, but the later sections were genuinely new to me. An easy five stars from me. I look forward to whatever the author writes next.

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

There is a particular kind of technical book that is dense without being difficult, and this is one of them. The examples are small enough to type out and experiment with, which is exactly what I want from a book like this. 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.

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

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 early chapters move quickly through material I already knew, but the later sections were genuinely new to me. The explanations are careful without being condescending, which is a difficult balance to strike. The author avoids over-explaining, which keeps the pace up but means you need to pay attention. Recommended, with the caveat that it is not a gentle introduction.

Strong content, uneven pacing. I would still recommend it.

There is a particular kind of technical book that is dense without being difficult, and this is one of them. It is denser than the page count suggests, and I found myself slowing down around the middle. It is denser than the page count suggests, and I found myself slowing down around the middle. A good addition to a technical library, as long as you know what you are buying.

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

I was looking for something that would bridge the gap between tutorials and proper reference material, and this does that well. The balance between theory and practice is well judged; neither side dominates. The index and cross-references are surprisingly good, which matters for a book I will come back to. There is a section near the end that ties several earlier ideas together in a way I had not seen before. This is the book I wish had existed when I started working with ai & machine learning.

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

I had been on the fence about this one for a while, and I should have bought it sooner. A few of the examples could be more realistic, but the underlying points come across clearly. There is a section near the end that ties several earlier ideas together in a way I had not seen before. I have already recommended it to two colleagues and will recommend it to more.