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ANOTHER PERSPECTIVE
From the review collection
Reader review5 / 5
Exactly what I was looking for
Genuinely excellent — I finished it in a week and immediately started again.
A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. The code samples assume a particular environment, which took a bit of fiddling to get running properly. Some of the diagrams are dense and I had to reread a few sections, though that may just be me. This is the book I wish had existed when I started working with ai & machine learning.
A genuinely enjoyable read that also taught me a great deal.
I had been on the fence about this one for a while, and I should have bought it sooner. The exercises at the end of each chapter are worth doing — they caught a few misconceptions I did not know I had. The writing is direct and does not waste space on filler, which I value in a technical book. The exercises at the end of each chapter are worth doing — they caught a few misconceptions I did not know I had. I have already recommended it to two colleagues and will recommend it to more.
Diane BaileyMachine learning engineer · Buenos Aires, AR
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.
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.
Well worth picking up if you already have the basics.
I had been on the fence about this one for a while, and I should have bought it sooner. 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. I particularly liked the way the author builds up from simple cases before introducing the harder material. Recommended, with the caveat that it is not a gentle introduction.
This is the one to get if you are serious about computational biology.
A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. The early chapters move quickly through material I already knew, but the later sections were genuinely 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. An easy five stars from me. I look forward to whatever the author writes next.
