Building and Analyzing Recommender Systems with the Surprise Library

Have you ever wondered how Netflix knows which movies to recommend to you? Or how Amazon knows which products you might be interested in? The answer is, of course, with recommender systems.

In this tutorial, we’ll use Surprise, a Python SciKit for building and analyzing recommender systems that deal with explicit rating data. This will enable us to use small, synthetic datasets to see how to handle the data in different kinds of contexts—such as restaurants and dating—and even how to use collaborative filtering to make predictions across different kinds of items.