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Online recommender systems help users find movies, jobs, restaurants—even romance! There’s an art in combining statistics, demographics, and query terms to achieve results that will delight them. Learn to build a recommender system the right way: it can make or break your application!
Practical Recommender Systems explains how recommender systems work and shows how to create and apply them for your site. After covering the basics, you’ll see how to collect user data and produce personalized recommendations. You’ll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book covers scaling problems and other issues you’ll encounter as your site grows.
We interviewed Kim as a part of our Six Questions series. Check it out here.
Covers the technical background and demonstrates implementations in clear and concise Python code.
Have you wondered how Amazon and Netflix learn your tastes in products and movies, and provide relevant recommendations? This book explains how it’s done!
Everything about recommender systems, from entry-level to advanced concepts.
A great and practical deep dive into recommender systems!
Practical Recommender Systems ebook for free