November 2018
Intermediate to advanced
322 pages
7h 54m
English
Content preview from TensorFlow Machine Learning Projects
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Hybrid systems
Hybrid systems leverage the power of both content-based and collaborative filtering by combing both methods. There are many ways hybrid systems are implemented, such as:
- Creating ensembles of content-based and collaborative filtering algorithms and combining the recommendations of both types of algorithms
- Enhancing collaborative filtering with content details and user information
- Adding user-item interaction models to content-based filtering algorithms
The reader is encouraged to explore more about the three kinds of recommendation systems. We'll explore how to build recommendation systems with matrix factorization and neural networks in the Retailrocket dataset example in the following section.
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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.