November 2018
Beginner to intermediate
568 pages
15h 59m
English
Content preview from Data Science, 2nd Edition
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Chapter 11
Recommendation Engines
Abstract
The advent of the digital economy has exponentially increased the choices of available items to customers, which can be overwhelming. Personalized recommendation lists help by narrowing the choices to a few items relevant to a particular user and aid users in making the final consumption decision. Recommendation lists, created by Recommendation engines, are one of the most prolific utilities of machine learning in everyday experience. Recommendation engines are a class of machine learning techniques that predict a user preference for an item. There are a wide range of techniques available to build a recommendation engine. This chapter discusses the most common methods starting with Collaborative Filtering ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.