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.
Acerca de este Curso
- 5 stars53,48 %
- 4 stars29,23 %
- 3 stars11,62 %
- 2 stars2,65 %
- 1 star2,99 %
Principales reseñas sobre NEAREST NEIGHBOR COLLABORATIVE FILTERING
Very good course, there is a glaring error in Week 4s assignment. But if you check the forums it can be easily solved
I love it. Would be cool to be able download all materials in one big .zip file (e.g for searching using grep) ;-)
Very satisfied to do this, the videos are too long, very good quality and a lot of practical information.
I love it!
Extremely informative course! It would be great if the assignments are created on python or R in the next season's offering. Thanks for the knowledge!
Acerca de Programa especializado: Sistemas de recomendación
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