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Nearest Neighbor Collaborative Filtering に戻る

ミネソタ大学(University of Minnesota) による Nearest Neighbor Collaborative Filtering の受講者のレビューおよびフィードバック

4.3
296件の評価
67件のレビュー

コースについて

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....

人気のレビュー

NS

2019年12月11日

i found this course very helpful and informative. it explains the theory while providing real-world examples on recommender systems. the assignment helps in clearing up any confusion with the material

SS

2019年3月30日

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.

フィルター:

Nearest Neighbor Collaborative Filtering: 26 - 50 / 67 レビュー

by Ayoub B

2020年9月23日

I found this course very helpful and informative. it explains the theory while providing real-world examples on recommender systems. the assignment helps in clearing up any confusion with the material. Also, the Honors track assignments are very good, although I like using Java but would love to use Python instead.

by Keshaw S

2018年2月13日

All in all, it is a comprehensive introduction to collaborative filtering. It allows the reader which paradigms and what tools to use in specific situations. I still have some complains with the excel assignments though.

by Nesreen S

2019年12月12日

i found this course very helpful and informative. it explains the theory while providing real-world examples on recommender systems. the assignment helps in clearing up any confusion with the material

by Sorratat S

2019年3月31日

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.

by Hossein E

2017年12月13日

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 !

by Ashwin R

2017年8月4日

Awesome as always, Joe and Michael rock. The interview with Brad Miller was stellar, felt like listening to the legends of rock-n-roll!

by Christian J

2017年7月17日

Very good course, there is a glaring error in Week 4s assignment. But if you check the forums it can be easily solved

by Dan R

2017年6月15日

Very satisfied to do this, the videos are too long, very good quality and a lot of practical information.

I love it!

by Pawel S

2017年1月8日

I love it. Would be cool to be able download all materials in one big .zip file (e.g for searching using grep) ;-)

by Sanjay K

2018年1月16日

Provides a good overview of item based and user based collaborative filtering approaches.

by Seema P

2017年2月14日

Awesome Professors!Great Material.Very thankful to Coursera for providing this course.

by Apurva D

2017年8月3日

Loved it...many thanks Prof. Joe for bringing this content to Coursera

by Light0617

2017年7月20日

a great class, I learned some insight in these algorithms

by Hagay L

2019年7月8日

Great learning experience about collaborative filtering!

by Ben C

2017年11月17日

Exercises take time but really helpful.

by srikalyan

2017年6月13日

Very good assignments, honors track.

by Xin X

2017年10月23日

in-depth and well-made to follow

by Blancher S

2022年4月8日

old, but very clear

by Xinzhi Z

2019年7月23日

Nice course!

by Sushmita B

2020年6月9日

excellent

by Twinkle

2018年4月30日

very nice

by Andrew W

2018年1月20日

Thank you for this course -- it opened my eyes to the universal applicability of recommender systems in tech applications.

My feedback is that you could do more to tie the *implementation* to the theory and real-life applications you discuss. You have many great lectures talking about how these systems were implemented, qualitative differences, subtle differences, and interviewing people to give us perspectives. But then the videos on implementation (including working through the equations) are pretty sparse and short. I felt like I'm "on my own" to figure out how to go implement these in real life. The problem sets cover one test case, and that's it. I think you could update the lectures to focus more on different algorithms / equations in different scenarios, rather than just talking qualitatively about them.

Regardless thank you! I deeply appreciate this course and what you've done. I plan to help my Consulting clients directly based on what I learned from you.

by Yury Z

2018年3月22日

The topics I am interested in covered by people who definitely has related expertise. But overall quality of the teaching materials expected to be higher. Forum is also a little bit deserted, although contains some critical hints to pass the assignments (such a hints worth to be included in the assignment descriptions itself). I want to support the course, and it is pity to give it only 4 of 5 stars, but I really expect more quality from the course I paid for.

by Jan Z

2016年11月10日

Excellent course providing not only the knowledge of algorithms but also useful insights into developing and maintaining recommender systems. Only thing that could use some work is the assignments. Spreadsheet assignment in week 4 is poorly designed (as evidenced by many forum threads with people not knowing what is it that the authors actually want). Other than that, that was an extremely helpful course.

by Siwei Y

2016年11月27日

Overall , it is a very interesting course.

But I would like to say , that there are too many interviews. I think that it is a little bit difficult for some non-native speaker to understand the main and important things from the interview, because some interviewers talked in a very loose way. So I would suggest our teacher , to summarize the main points of those interview in a better way .