101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback)

Solid and well-organised. A couple of chapters dragged a little.

I picked this up after getting stuck on a project and it turned out to be exactly the right book at the right time. The chapters on artificial intelligence 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. The code samples assume a particular environment, which took a bit of fiddling to get running properly. A good addition to a technical library, as long as you know what you are buying.

Worth every page. I have already recommended it to two colleagues.

A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. A couple of chapters felt like they could have been merged, but that is a minor complaint. I particularly liked the way the author builds up from simple cases before introducing the harder material. There is a section near the end that ties several earlier ideas together in a way I had not seen before. An easy five stars from me. I look forward to whatever the author writes next.

I have read a lot of books on this subject and this is the clearest.

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 progression from chapter to chapter is well thought out; nothing feels out of order. I particularly liked the way the author builds up from simple cases before introducing the harder material. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.