Preface

In recent years, popular imagination has become fascinated by machine learning. The discipline has found a variety of applications. Some of these applications, such as spam filtering, are ubiquitous and have been rendered mundane by their successes. Many other applications have only recently been conceived, and hint at machine learning's potential.

In this book, we will examine several machine learning models and learning algorithms. We will discuss tasks that machine learning is commonly applied to, and we will learn to measure the performance of machine learning systems. We will work with a popular library for the Python programming language called scikit-learn, which has assembled state-of-the-art implementations of many machine learning algorithms under an intuitive and versatile API.