Clojure Data Analysis Cookbook by Eric Rochester
My rating: 5 of 5 stars
This book is a good tutorial on data science using Clojure. It starts with working with data (access and cleaning up), then the various chapters cover a range of tasks from focusing on numeric computing (performance, parallel processing), statistics (Incanter and other numerical libraries), working with other numerical software (Mathematica and R), graphics, and the web. The topics are actually a fairly complete look at data science, so it feels more like a tutorial than a cookbook.
I found this to be a great text on working with data in Clojure. My background is in technical computing, mostly R and Python although I also use C, Java, and Fortran as needed. I've been dabbling in Clojure, but I had not made the jump from doing tutorials and exercises in Clojure to doing something for real. Working through this book has improved my skills in setting Clojure up and using it for real tasks. The book code also provides a nice example of good programming style (I think) that I can see myself trying to emulate.
A book on data science is necessarily about the practical details of implementation, not about mathematical and statistical methods. Presumably, the reader has another source about the details of various statistical and machine learning methods that they can use to figure out what to do, then the Clojure and Incanter API documents tell you how to do it, and this book is about how to do the 80% of data science that is not about implementing the algorithm, but about how to manage the data, then work to communicate the results of the algorithm in understandable ways. This book is probably what brings me from dabbling in Clojure to being able to use Clojure for real tasks. Well done.
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