Overview

Description Recommender systems are practically a necessity for keeping a site’s content current, useful, and interesting to visitors. Recommender systems are everywhere, helping you find everything from movies to jobs, restaurants to hospitals, even romance. Practical Recommender Systems goes behind the curtain to show readers how recommender systems work and, more importantly, how to create and apply them for their site. This hands-on guide covers scaling problems and other issues they may encounter as their site grows.   Key features • A behind the scenes look at recommender systems • Hands-on lessons • Step-by-step guide   Audience This book assumes you're comfortable reading code in Python and have some experience with databases.   About the Technology Using behavioral and demographic data, these systems make predictions about what users will be most interested in at a particular time, resulting in high-quality, ordered, personalized suggestions.  

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9781617292705

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Kim Falk is a Data Scientist at Adform, where he is working on recommender systems. He has experience in providing recommendations for large entertainment companies and working with big data solutions.

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