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学生对 明尼苏达大学 提供的 Introduction to Recommender Systems: Non-Personalized and Content-Based 的评价和反馈

4.5
459 个评分
93 个审阅

课程概述

This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations. After completing this course, you will be able to compute a variety of recommendations from datasets using basic spreadsheet tools, and if you complete the honors track you will also have programmed these recommendations using the open source LensKit recommender toolkit. In addition to detailed lectures and interactive exercises, this course features interviews with several leaders in research and practice on advanced topics and current directions in recommender systems....

热门审阅

BS

Feb 13, 2019

One of the best courses I have taken on Coursera. Choosing Java for the lab exercises makes them inaccessible for many data scientists. Consider providing a Python version.

IP

Sep 19, 2016

it's a fantastic course that gives you a good idea of what the objectives of recommender systems are and some intuition on the way how it can be accomplished.

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26 - Introduction to Recommender Systems: Non-Personalized and Content-Based 的 50 个评论(共 89 个)

创建者 Igor P

Sep 19, 2016

it's a fantastic course that gives you a good idea of what the objectives of recommender systems are and some intuition on the way how it can be accomplished.

创建者 Fernando C

Nov 08, 2016

pues esta bien chido el curso

创建者 ignacio g

Oct 27, 2016

The course es really helpfull to understand how the recommender system works and what points yo have to take care when you have to implement

创建者 Biswa s

Mar 28, 2018

Good overview on the recommend-er system.

创建者 Yury Z

Mar 08, 2018

Informative and helpfull for me as recommender systems practitioner. Even for things I've knew already the authors offer clean and holistic base. Surprisingly the honour track programming assignments was pretty challenging.

创建者 HN M

Aug 28, 2017

great!

创建者 Francisco C

Mar 21, 2017

Excelente curso, presenta una vista amplia de técnicas para la implementación de sistemas de recomendación, lo recomiendo totalmente.

创建者 Apurva D

Aug 03, 2017

Awesome content...loved the industry expert interviews....

创建者 Dame N

Nov 24, 2017

Thank you for your course, very Helpfull for those who are keep in touch with recommender System engine. This is a very cool Introduction course.

创建者 Garvit G

Mar 22, 2018

awesome course.

创建者 shayue

Apr 11, 2019

Really Good! I think it will be helpful to me and take a job for me!

创建者 vibhor n

Jun 03, 2019

A good introduction to the basic concepts of recommender systems. Loved the idea of having excel work assignments. For someone just wanting a quick learning of the concepts doesn't have to go through all the Java stuff

创建者 Xinzhi Z

Jul 18, 2019

Great course. I really appreciated the efforts spent by the course team.

创建者 Julia K

Sep 09, 2019

This course is a wonderful logical informative introduction to several basic types of recommender systems. It is a great part to start! The instructors a clear and well organized. Some assignments were a little bit awkward but overall they

创建者 Su L

Aug 23, 2019

great course, learnt a lot, thanks!

创建者 Muhammad Z H

Sep 17, 2019

Learnt alot

创建者 P S

Sep 26, 2019

Nice course

创建者 Kevin R

Oct 09, 2017

Well-designed assignments and instructive programming exercises in the honors track.

创建者 Nesreen S

Nov 14, 2019

I found this course very informative. with real-life examples of the recommender's use case and who it can be implemented. I loved that it has an excel assignment to get an intuition about the concepts allowing business-like and non-techincal audiences to understand and practice the concepts. I found the honor track and assignment though challenging but very important and helpful though the documentation of lenskit was not very clear.

it was enjoyable and very useful.

创建者 jonghee

Oct 29, 2019

good lecture

创建者 王嘉奕

Nov 06, 2019

Excellent course which helps me a lot.

创建者 Gurupratap S M

Dec 02, 2019

Really a very nice course with great attention to detail. The guest interviews were also superb and gave me exposure to different areas of research in recommender systems in general. Both Michael and Joe are experts and provide deep insights with plenty of examples and study cases. Honors exercises are another added bonus to practice and get hands on experience. I had already deployed a recommender system in production am glad to continue learning and learn different techniques. Thank you once again

创建者 LI Z

Jan 01, 2019

Awesome lecture and demonstration.

Here are some suggestions, first I think this course may spend too much time on non-trivial parts and some parts can be neglected; second, the programming assignment lacks a lot of supplementary tutorial for people who are not familiar with Java and LensKit package.

创建者 ignacio v

Feb 04, 2019

done it by audit, thnks!!! great stuff guys... but should do some practice in python!