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.
À propos de ce cours
- 5 stars53,48 %
- 4 stars29,23 %
- 3 stars11,62 %
- 2 stars2,65 %
- 1 star2,99 %
Meilleurs avis pour NEAREST NEIGHBOR COLLABORATIVE FILTERING
Very satisfied to do this, the videos are too long, very good quality and a lot of practical information.
I love it!
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 !
I found this course very informative and clears lot of concept in Item based and used based collaborative filtering. Spreadsheet assignment helped me to clearly understand the algorithms.
a great class, I learned some insight in these algorithms
À propos du Spécialisation Systèmes de recommandation
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