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Introduction to Recommender Systems: Non-Personalized and Content-Based, 明尼苏达大学

4.5
387 個評分
76 個審閱

課程信息

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....

熱門審閱

創建者 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.

創建者 DP

Dec 08, 2017

Nice introduction to recommender systems for those who have never heard about it before. No complex mathematical formula (which can also be seen by some as a downside).

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72 個審閱

創建者 shayue

Apr 11, 2019

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

創建者 Joeri Kiekens

Mar 23, 2019

It would be nice to have a hierarchical overview of the recommender systems. It's easy to get lost which is a subcategory of which. Thanks for the course!

創建者

Feb 28, 2019

not so deep

創建者 Jon Holdship

Feb 14, 2019

The content of this course is solid. It's a good introduction to content based and non-personailzed recommender systems. However, the presentation is poor. The course is largely based around videos which appear to be single takes. Snappier, well edited videos would have been better and, as a result, I often found myself skimming the transcripts rather than watching the videos.

創建者 Benjamin S. Skrainka

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.

創建者 Mustafa SENHAJI

Feb 08, 2019

Great course

創建者 ignacio vilieri

Feb 04, 2019

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

創建者 Mai Hong Son

Jan 20, 2019

good exercises & lectures

創建者 Md. Shamsur Rahim

Jan 05, 2019

The lecturer were very lengthy, at least for me. I find it difficult to concentrate.

創建者 LI ZONGXI

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.