FOREWORD

 

Recommender systems dictate the stream of content displayed to us each day and their impact on online behavior is second to none. From relevant friend suggestions on Facebook to product recommendations on Amazon, there’s no missing their presence and online sway. Whether you agree or disagree with this method of marketing, there’s no arguing its effectiveness. If mass adoption doesn’t convince you, take a look at what you’ve recently viewed and bought online. There’s a strong chance that at least some of your online activities, including finding this book, originated from algorithm-backed recommendations.

These data-driven systems are eroding the dominance of traditional search while aiding the discoverability of items that might not otherwise have been found. As a breakaway branch of machine learning, it’s more important than ever to understand how these models work and how to code your own basic recommender system.

This book is designed for beginners with partial background knowledge of data science and machine learning, including statistics and computing programming using Python. If this is your first foray into data science, you may want to spend a few hours reading my first book Machine Learning for Absolute Beginners before you get started here.