Reader reviews

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 author clearly knows the subject deeply and has thought hard about how to teach it. The author avoids over-explaining, which keeps the pace up but means you need to pay attention. Solid, and I would buy another book from this author without hesitation.

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

This is the third book I have read on ai & machine learning this year, and it is comfortably the best of them. The early chapters move quickly through material I already knew, but the later sections were genuinely new to me. 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.

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

This is the third book I have read on ai & machine learning this year, and it is comfortably the best of them. I particularly liked the way the author builds up from simple cases before introducing the harder material. 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. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.

Good in places. I would borrow it before buying if you can.

I had been on the fence about this one for a while, and I should have bought it sooner. The author is unusually honest about where the simplifications break down, which I appreciated. The early chapters move quickly through material I already knew, but the later sections were genuinely new to me. Fine, but there are stronger books on the same subject if you look around.

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

I picked this up after getting stuck on a project and it turned out to be exactly the right book at the right time. I found myself making notes in the margins, which is always a good sign. The code samples assume a particular environment, which took a bit of fiddling to get running properly. The chapters on ai & machine learning are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. Worth the money and the reading time, without hesitation.

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

I bought this on a whim after seeing it mentioned in a forum thread, and I am glad I did. I appreciated the honesty about what the book does not cover — it saved me from expecting things that were not there. The index and cross-references are surprisingly good, which matters for a book I will come back to. 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.