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.
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TOP REVIEWS FROM NEAREST NEIGHBOR COLLABORATIVE FILTERING
Loved it...many thanks Prof. Joe for bringing this content to Coursera
Awesome Professors!Great Material.Very thankful to Coursera for providing this course.
Thank you so very much to open my eye see more view of recommendation field not only algorithms but use case and many trouble-shooting in worldwide business, moreover interview with noble professor.
Very satisfied to do this, the videos are too long, very good quality and a lot of practical information.
I love it!
About the Recommender Systems Specialization
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