Book Review: Learning scikit-learn: Machine Learning in Python

Recently I was given a reviewer's copy of Learning scikit-learn: Machine Learning in Python from the publisher Packt Pub. The fact that I was given a copy of the book in exchange for a written review has in no way influenced my rating of the book.

Learning scikit-learn: Machine Learning in Python by Raúl Garreta and Guillermo Moncecchi is a book that gives you a quick introduction to the scikit-learn toolkit. At a total of 118 pages, this book is a quick and easy read. The authors don't go deep into depth behind the mathematics involved in the different machine learning techniques that they discuss, but then that's not the point of the book and could be seen as a plus to some.

I like the fact that they chose to distribute the code via the iPython notebook format so you can run the code inside a browser window (as long as you have the necessary dependencies installed). The authors walk you through installing most of the dependencies, but there are others that are left to the reader to install on their own, and because of that there were a couple of examples that didn't work properly when walking through them for me. This is in no way a problem with the book though and is easily fixed by downloading the missing Python modules.

I enjoyed walking through the examples and felt that the authors accomplished what they set out to do with this book and highly recommend it to those who want to get an introduction to scikit-learn.

Overall this is a great book and I definitely recommend it.

For those who like to see actual ratings, I give the book a 5 out of 5 stars.