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.
Об этом курсе
- 5 stars53,48 %
- 4 stars29,23 %
- 3 stars11,62 %
- 2 stars2,65 %
- 1 star2,99 %
Лучшие отзывы о курсе NEAREST NEIGHBOR COLLABORATIVE FILTERING
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.
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.
Very good course, there is a glaring error in Week 4s assignment. But if you check the forums it can be easily solved
Very satisfied to do this, the videos are too long, very good quality and a lot of practical information.
I love it!
Специализация Рекомендательные системы: общие сведения
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