Are you envious when Amazon recommends its products or when Netflix is spot-on with a recommendation for a user? Then here’s your chance to learn how to add these skills to your repertoire. Reading this book will give you an understanding of what recommender systems are and how to apply them in practice. To make a recommender work, many things need to perform in concert. You need to understand how to collect data from your users and how to interpret it, and you need a toolbox of different recommender algorithms so you can choose the best one for your particular scenario. Most importantly, you need to understand how to evaluate whether your recommender system is doing its job well. All this and more is hidden within this book.
Practical Recommender Systems is primarily intended for developers who are interested in implementing a recommender. The book takes a practical approach and attempts to explain everything in normal, everyday language. There will be math and statistics, but both will be accompanied by figures and code. New data scientists will also benefit from this book as an introduction to recommender algorithms and to the infrastructure needed to get them up and running. Managers will find this book useful to get an overview of what a recommender system is and how it can be used in practice.