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.
- 5 stars53.48%
- 4 stars29.23%
- 3 stars11.62%
- 2 stars2.65%
- 1 star2.99%
NEAREST NEIGHBOR COLLABORATIVE FILTERING からの人気レビュー
Loved it...many thanks Prof. Joe for bringing this content to Coursera
Awesome as always, Joe and Michael rock. The interview with Brad Miller was stellar, felt like listening to the legends of rock-n-roll!
Very good course, there is a glaring error in Week 4s assignment. But if you check the forums it can be easily solved
Awesome Professors!Great Material.Very thankful to Coursera for providing this course.