WebGPU Data Visualization Cookbook (2nd Edition)

Very good, with a few caveats. The core material is strong.

I read this over a couple of weekends alongside a small side project, which turned out to be the ideal way to approach it. 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 progression from chapter to chapter is well thought out; nothing feels out of order. A good addition to a technical library, as long as you know what you are buying.

Recommended, with the caveat that it is not a gentle introduction.

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 index and cross-references are surprisingly good, which matters for a book I will come back to. I particularly liked the way the author builds up from simple cases before introducing the harder material. Worth picking up if you already have the basics. Set realistic expectations and you will get a lot out of it.

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

A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. 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. Worth the money and the reading time, without hesitation.