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%
来自NEAREST NEIGHBOR COLLABORATIVE FILTERING的热门评论
a great class, I learned some insight in these algorithms
Loved it...many thanks Prof. Joe for bringing this content to Coursera
Very satisfied to do this, the videos are too long, very good quality and a lot of practical information.
I love it!
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.