In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. You will explore and implement variations of the user-user algorithm, and will explore the benefits and drawbacks of the general approach. Then you will learn the widely-practiced item-item collaborative filtering algorithm, which identifies global product associations from user ratings, but uses these product associations to provide personalized recommendations based on a user's own product ratings.
About this Course
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- 4 stars29.23%
- 3 stars11.62%
- 2 stars2.65%
- 1 star2.99%
TOP REVIEWS FROM NEAREST NEIGHBOR COLLABORATIVE FILTERING
everything best. But technical support in Forum and when a student needs help when he is learning in Vienna alone is the worst
thanks very much !
Very good course, but the quiz on Week 4 is unclear
a great class, I learned some insight in these algorithms
i found this course very helpful and informative. it explains the theory while providing real-world examples on recommender systems. the assignment helps in clearing up any confusion with the material
About the Recommender Systems Specialization
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