"I found this book to be very useful. Before reading this text I had already read portions of Expert F#, and have an extensive background with the older SML language that F# and OCaml are related to. As someone who works in scientific computing, I have always wished for a reference that would explain how to use this family of languages in scientific contexts. This book provides an excellent discussion of this topic. The examples are familiar if you come from a scientific computing background, and it is useful to see examples framed in a mathematical or scientific context instead of the more abstract or simple examples found in texts aimed at more general audiences. I would highly recommend this book - it's a pleasure to read, and has proven to be a useful reference for me so far."
"In short, it is an excellent book and an invaluable resource for those working in quantitative computing.
The best feature of the book is its conciseness and clarity. Given F#’s immense multi-paradigm nature it is impossible to cover everything in only 300 pages, so the book skips object-oriented programming and doesn’t do a thorough job covering F# syntax. Rather, the book covers just enough F# to solve scientific problems using the functional style. (And highlights just how well suited for science F# truly is!)
This focus on scientific computing however is also the book’s main (potential) flaw. If you consider yourself a scientist, then this book will teach you everything you need to know about F#. But if you are a .NET developer looking to integrate F# into your projects, you might find the book’s coverage of the language a little lacking. (Specifically in how to do object-oriented programming in F#.)
What impressed me most was just how clear the examples were. I haven’t had a lot of functional programming experience before working on F#, and I found the examples in the book to be very instructive on how to write ‘good’ functional code."