A review is one perspective. Compare what readers say with the synopsis, publication details, and your own interests.
Try a topic plus an author, or use an ISBN for an edition. Need help choosing?
4293837 books to explore · Review entries are shown where available.
ANOTHER PERSPECTIVE
Perspectives on the books
Reader review5 / 5
A genuine pleasure to read
A superb guide. The examples are small but complete.
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 author avoids over-explaining, which keeps the pace up but means you need to pay attention. An easy five stars from me. I look forward to whatever the author writes next.
Finally, a book that treats webgpu with the care it deserves.
A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's 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 early chapters move quickly through material I already knew, but the later sections were genuinely new to me. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.
This is the one to get if you are serious about ai & machine learning.
I was looking for something that would bridge the gap between tutorials and proper reference material, and this does that well. Some terminology is introduced without much ceremony; I had to look a few things up along the way. The balance between theory and practice is well judged; neither side dominates. Worth the money and the reading time, without hesitation.
A superb guide. The examples are small but complete.
A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. I appreciated the honesty about what the book does not cover — it saved me from expecting things that were not there. The examples are small enough to type out and experiment with, which is exactly what I want from a book like this. The writing is direct and does not waste space on filler, which I value in a technical book. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.
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 book rewards careful reading. Skimming it would be a mistake. Worth the money and the reading time, without hesitation.
A genuinely enjoyable read that also taught me a great deal.
I was looking for something that would bridge the gap between tutorials and proper reference material, and this does that well. 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. I have already recommended it to two colleagues and will recommend it to more.
