Programming Machine Learning

I just received my copy of Programming Machine Learning, a book by Paolo Perrotta. I had the pleasure of being one of the technical reviewers of the draft and, while this is not the first book I read about Machine Learning, I must say it became one of my favorites.

Paolo promises, at the beginning of the book, to write a book meant for developers, and he delivers on that promise.

In his words,

This is the book I missed when I got started with machine learning: an introduction for developers, written in our own language. After reading it, you’ll be comfortable with the fundamentals, and able to write machine learning programs.

Programming Machine Learning is a book that teaches the foundations of ML by walking the reader through the process of implementing working solutions for a few concrete and specific use cases, such as predicting sales volume for a pizzeria, recognizing hand-written digits or classifying images.

Each chapter introduces a challenge, lays out the foundations of a technical implementation and explains the theoretical background behind the techniques adopted.

As a result, the book is much easier to follow than many others on this subject: even when diving deeper into the technical or mathematical aspects of any of the topics covered, the reader is able to build on the empirical intuition that comes from having implemented ML algorithms and having seen them in action. Every chapter is engaging, starting from the first ones, about trying to predict pizza sales via linear regression and simple perceptrons, to the last ones, leveraging Keras to classify images.

I found the overall approach quite novel and refreshing. I would definitely recommend Programming Machine Learning, especially if you are the type of engineer who generally enjoys learning by doing.