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Learner Reviews & Feedback for Introduction to Recommender Systems: Non-Personalized and Content-Based by University of Minnesota

4.5
stars
550 ratings
116 reviews

About the Course

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....

Top reviews

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.

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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101 - 112 of 112 Reviews for Introduction to Recommender Systems: Non-Personalized and Content-Based

By Anil S

Aug 28, 2020

Would be nice to complete the honours track using python.

By Aleshin A

May 18, 2018

It would be better to make practice on Python.

By Andre C

Mar 30, 2020

Great course

By Chunyang S

Feb 03, 2017

Generally I like the contents of this course. I particularly like that insights are provided in terms of what aspects to consider when designing a recommender system; pros and cons of different approaches. However I'm also extremely bored watching the videos because looking at the lectures reading the scripts (most of the time with very slow speed) is one of the quickest way to send people to sleep. I'd hope the lectures will improve their presenting skills.

Another comment is the honours track assignments should really be put into more thoughts. I passed them with 100% credit, but I didn't feel I gained a lot useful knowledge through this exercise. Generally it felt to me that the complexity of the implementation is much much more than needed in relation to the complexity of the problems. Eventually this assignment became grinding with Java's verbose, annoying syntax and unnecessary computations designed in lab instruction. For example, in the first programming assignment, why if the ModelProvider object already computed the entire map of ratings, and the map is directly needed in the Recommender object, the Model object only provide API to retrieve individual rating but not the entire map?! Isn't it a wasteful computation to reconstruct the rating map? So I doubt the structural design of the program is sensible, or the expected solution would actually be done in real applications. Also I think Java is just a really out-dated, bulky language to work with in this kind of task. It really makes the assignment experience awful.

By Akash S C

Jun 22, 2019

Good course for basic intro to recommender system. However, some basic problems - videos are too long and Java for programming assignment was a huge disappointment. i tried picking the lenskit assignment with java but decided to get rid of it and replicated the assignment in python instead. it was taking too much time to learn Java back which will never be used in regular work for data science. python or R should have been used for prog assignment. time to update the course.

By Sachin S

Oct 31, 2016

I expected a lot from this course but it could have been a lot better - lengthy videos, not trying to explain the concepts in an understandable ways. Ended up confusing with various interviews and what are differences between various content based recommenders. The programming exercises were good and provided a good overview.

By Paulo E d V

Dec 08, 2016

Ok, it's an introduction, but it could at least show us some math or pseudocodes. A part from that, the course is really awesome. Well structured classes, good explanations and incredible interviews

By Ruth B

Aug 13, 2017

Not bad for an introduction, but I would have prefered it to be more technical

By Lucas P B

Sep 04, 2019

Was expecting programming activities in Python or R, not in Java =/

By AISHWARY B

Mar 29, 2020

Coding assignment should not be just restricted to java

By MinhyePark

Feb 27, 2020

수학개념이 부족해서 조금 추상적으로 이해하게 되었습니다.