Reader reviews

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

I picked this up after getting stuck on a project and it turned out to be exactly the right book at the right time. I found myself making notes in the margins, which is always a good sign. The author clearly knows the subject deeply and has thought hard about how to teach it. The author clearly knows the subject deeply and has thought hard about how to teach it. Good value for the price and worth the time it takes to work through properly.

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

I was looking for something that would bridge the gap between tutorials and proper reference material, and this does that well. The author is unusually honest about where the simplifications break down, which I appreciated. The book rewards careful reading. Skimming it would be a mistake. Worth picking up if you already have the basics. Set realistic expectations and you will get a lot out of it.

Finally, a book that treats ai & machine learning with the care it deserves.

There is a particular kind of technical book that is dense without being difficult, and this is one of them. The explanations are careful without being condescending, which is a difficult balance to strike. A few of the examples could be more realistic, but the underlying points come across clearly. I appreciated the honesty about what the book does not cover — it saved me from expecting things that were not there. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.

I got a lot out of this, even if a few sections felt rushed.

There is a particular kind of technical book that is dense without being difficult, and this is one of them. The author is unusually honest about where the simplifications break down, which I appreciated. The book rewards careful reading. Skimming it would be a mistake. Four stars, and I suspect a second edition could easily push it to five.

The clearest explanation of computational biology I have come across.

I have been working with computational biology for a few years now and I still found plenty here that was new to me. The chapters on computational biology are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. There is a section near the end that ties several earlier ideas together in a way I had not seen before. This is the book I wish had existed when I started working with computational biology.

Not quite what I expected from the description, but there is material here.

There is a particular kind of technical book that is dense without being difficult, and this is one of them. The explanations are careful without being condescending, which is a difficult balance to strike. The writing is direct and does not waste space on filler, which I value in a technical book. Some of the diagrams are dense and I had to reread a few sections, though that may just be me. Fine, but there are stronger books on the same subject if you look around.