Learn Neural Networks and Deep Learning with WebGPU and Compute Shaders

An enjoyable and informative read, though it could have been shorter.

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. The balance between theory and practice is well judged; neither side dominates. A good addition to a technical library, as long as you know what you are buying.

A superb guide. The examples are small but complete.

I read this over a couple of weekends alongside a small side project, which turned out to be the ideal way to approach it. The code samples assume a particular environment, which took a bit of fiddling to get running properly. 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.

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

I have been working with ai & machine learning for a few years now and I still found plenty here that was new to me. The chapters on ai & machine learning are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. A couple of chapters felt like they could have been merged, but that is a minor complaint. It is denser than the page count suggests, and I found myself slowing down around the middle. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.