WebGPU Data Visualization Cookbook (2nd Edition)

Some sections were excellent and others felt like filler.

I bought this on a whim after seeing it mentioned in a forum thread, and I am glad I did. It is denser than the page count suggests, and I found myself slowing down around the middle. I appreciated the honesty about what the book does not cover — it saved me from expecting things that were not there. The author is unusually honest about where the simplifications break down, which I appreciated. Useful as a reference, less so as a straight read from cover to cover.

Mixed feelings. The good parts are genuinely good; the rest is forgettable.

There is a particular kind of technical book that is dense without being difficult, and this is one of them. The code samples assume a particular environment, which took a bit of fiddling to get running properly. Some of the material is available elsewhere, but rarely presented this clearly. The writing is direct and does not waste space on filler, which I value in a technical book. Fine, but there are stronger books on the same subject if you look around.

Exactly the book I needed. Straight to the point and genuinely useful.

I had been on the fence about this one for a while, and I should have bought it sooner. The chapters on ai & machine learning are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. Some of the diagrams are dense and I had to reread a few sections, though that may just be me. I have already recommended it to two colleagues and will recommend it to more.