Grow a question. Pick a good book.

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

A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. 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. The author is unusually honest about where the simplifications break down, which I appreciated. A good addition to a technical library, as long as you know what you are buying.

Strong content, uneven pacing. I would still recommend it.

I had been on the fence about this one for a while, and I should have bought it sooner. The explanations are careful without being condescending, which is a difficult balance to strike. I particularly liked the way the author builds up from simple cases before introducing the harder material. The chapters on ai & machine learning are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. Good value for the price and worth the time it takes to work through properly.

A useful guide. The examples assume a particular environment, but that is fixable.

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. A good addition to a technical library, as long as you know what you are buying.