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Hands-On Recommendation Systems with Python

You're reading from   Hands-On Recommendation Systems with Python Start building powerful and personalized, recommendation engines with Python

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781788993753
Length 146 pages
Edition 1st Edition
Languages
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Author (1):
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Rounak Banik Rounak Banik
Author Profile Icon Rounak Banik
Rounak Banik
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Introduction

As already mentioned a couple of times, hybrid recommenders are extremely powerful, robust systems that combine various simpler models to give us predictions. There is no single way in which a hybrid model could do this; some hybrids predict using content and collaborative filtering techniques separately to produce results. Some others introduce content-based techniques into collaborative filters and vice versa.

Netflix is a very good example of a hybrid recommender. Netflix employs content-based techniques when it shows you similar movies to a movie you're watching (the MORE LIKE THIS section), as shown in the following screenshot:

Here, we can see that while watching Ratatouille, Netflix recommends movies to me that are very similar to Ratatouille. All the top five recommended movies are all animated and produced by Disney Pixar.

However, animated movies...

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