March 2018
Intermediate to advanced
484 pages
10h 31m
English
In this section, we will see how to utilize collaborative filtering to develop a recommendation engine. However, before that let's discuss the utility matrix of preferences.
In a collaborative filtering-based recommendation system, there are dimensions of entities: users and items (items refer to products, such as movies, games, and songs). As a user, you might have preferences for certain items. Therefore, these preferences must be extracted out of the data about items, users, or ratings. This data is often represented as a utility matrix, such as a user-item pair. This type of value can represent what is known about the degree of preference that the user has for a particular ...
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