The structure of the book
In this book, we will learn about popular recommender systems that are used the most. We will also look into different machine learning techniques used when building recommendation engines with sample code.
The book is divided into 5 chapters:
- In Chapter 1, Getting Started with Recommender Systems, you will get a general introduction to recommender systems, such as collaborative filtering recommender systems, content-based recommender systems, knowledge-based recommender systems, and hybrid systems; it will also include a brief definition, real-world examples, and brief details of what one will be learning while building a recommender system.
- In Chapter 2, Data Mining Techniques Used in Recommender Systems, gives you an ...