Part 1. Getting ready for recommender systems

Using recommender systems and, in fact, most machine learning methods in production isn’t only about implementing the best algorithm, it’s about understanding your users and the domain.

Chapters 1–6, part 1 of Practical Recommender Systems, introduce you to the recommender system ecosystem and infrastructures. You’ll learn how to collect data and how to use it when you add a recommender system to your application. You’ll learn the difference between a recommendation and an advertisement, and between a personal recommendation and a non-personal one. You’ll also learn how to gather data to build your own recommender system.