Algorithms to Live By

I picked up this book at the recommendation of a friend, and as someone who studied Computer Science at university, I wanted to love it. I did find this book interesting, but I also found myself skimming a lot. I felt that some of the chapters were quite long and I lost interest towards the end. I'm not sure it got the right balance between hard CS concepts and their real-life applications.

I enjoyed the first chapter and the chapter on distribution curves (standard, exponential, Erlang) and corresponding prediction models.

Much of the rest of the book was frustrating to read. It tries to cover so many topics so thinly that it barely gets into one observation before it leaves it behind for another.

On page 74 it starts into an interesting discussion of sports tournaments and mentions Lewis Carroll's pamphlet on lawn tennis brackets. But then, in less than a page, it skips over Carroll's proposed solution (because it's an “awkward take”).

Or the page on unlimited vacation time for employees (which features a quote from a friend of mine) barely addresses a single objection and then moves on to other topics.

Instead of introducing readers to the complexity and nuances of the difficult and often decades-long dilemmas of computer science, it turns them all into misleading single page summaries.

I would have preferred to read a book where they picked half as many topics and discussed them more thoroughly.

Reading this book confirmed a new personal approach to avoiding books that will be disappointing:

- About 250 pages long
- Subject is vaguely scientific or mathematical
- Uses the Gotham font or another geometric sans anywhere

This book satisfies all three and now I know that I should avoid buying this kind of book.

I picked up this book at the recommendation of a friend, and as someone who studied Computer Science at university, I wanted to love it. I did find this book interesting, but I also found myself skimming a lot. I felt that some of the chapters were quite long and I lost interest towards the end. I'm not sure it got the right balance between hard CS concepts and their real-life applications.

Interesting read. The discussion of how some CS algorithms mirror behaviors seen in nature and how some CS algorithms have influenced solutions in a non-CS context was interested. In some cases material seemed to be there as filler (a general discussion of an algorithm without really explaining how it had anything to do with non-CS things), and in a few cases things were stated in a way that was oversimplified (given the context). All in all, a good, light read.