Book Image

Hands-On Recommendation Systems with Python

By : Rounak Banik
Book Image

Hands-On Recommendation Systems with Python

By: Rounak Banik

Overview of this book

Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform. This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—you'll get started with building and learning about recommenders as quickly as possible.. In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques  With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains.
Table of Contents (9 chapters)

Case study – Building a hybrid model

In this section, let's build a content-based model that incorporates some collaborative filtering techniques into it.

Imagine that you have built a website like Netflix. Every time a user watches a movie, you want to display a list of recommendations in the side pane (like YouTube). At first glance, a content-based recommender seems appropriate for this task. This is because, if the person is currently watching something they find interesting, they will be more inclined to watch something similar to it.

Let's say our user is watching The Dark Knight. Since this is a Batman movie, our content-based recommender is likely to recommend other Batman (or superhero) movies regardless of quality. This may not always lead to the best recommendations. For instance, most people who like The Dark Knight do not rate Batman and Robin very...