Reader reviews

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.

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.

I have read a lot of books on this subject and this is the clearest.

I came to this book already familiar with the basics, and it still had plenty to offer. I found myself making notes in the margins, which is always a good sign. The early chapters move quickly through material I already knew, but the later sections were genuinely new to me. Worth the money and the reading time, without hesitation.

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

A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. The author avoids over-explaining, which keeps the pace up but means you need to pay attention. The writing is direct and does not waste space on filler, which I value in a technical book. The code samples assume a particular environment, which took a bit of fiddling to get running properly. Borrow it first if you can, or at least check the table of contents carefully before buying.

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.

Outstanding. I kept finding reasons to come back to it.

This is the third book I have read on ai & machine learning this year, and it is comfortably the best of them. A few of the examples could be more realistic, but the underlying points come across clearly. A couple of chapters felt like they could have been merged, but that is a minor complaint. The code samples assume a particular environment, which took a bit of fiddling to get running properly. One of those books that pays for itself within the first few chapters. Highly recommended.