Lecture

Recommender Systems: Basics and Techniques

Description

This lecture introduces recommender systems, covering collaborative filtering and content-based methods. It explains user-based and item-based collaborative filtering, addressing cold start problems and scalability. The lecture also discusses similarity metrics, aggregation of ratings, and making predictions.

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