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

4.5
stars
555 ratings
117 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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26 - 50 of 113 Reviews for Introduction to Recommender Systems: Non-Personalized and Content-Based

By sidra n

Aug 15, 2018

I would like to have more detail and help for honors track especially for people like me who do not have much programming experience and want to learn how to implement recommender system. I am unable to solve the assignment and i still need some help. Would be great if the solutions of the honors track should be available to those who want to learn and not just for the sake of getting certificate

By Shantanu B

Mar 17, 2020

This course takes me through many of the techniques that started at the dawn of recommendation systems and some which are still going strong in certain domains and certain scale. Rather than just concentrating on the numerical aspects of the topic, there has been a great emphasis on learning the tricks of the trade and the aspects that should be kept in mind while employing the techniques.

By Muffaddal Q

Dec 12, 2019

a good course with detail explanation on many aspect of non-personalized and content based recommendations. Interviews with experts with excellent. Helped to learn how professionals are solving different problems related to recommendations in their respective fields.

By 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

By Rosni L

Oct 04, 2016

This course is really helpful in understanding the state of the art of non-personalized and content-based recommender systems. More it is invaluable to have changes to get the latest information from the expert through the interviews.

By 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.

By 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

By Yuncheng W

Nov 03, 2016

I think this is an amazing course for beginners who are interested in recommender systems, I strongly recommend this course to the students and engineers who are working on recommender systems.

By Danilo L A

Sep 16, 2020

Awesome. All concepts were very well explained in an understandable and didatical language.

Loved the interviews with all the specialists.

I've learned so much, thanks for this course!

By Daniel P

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).

By 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.

By Sonia F

Feb 06, 2017

Un profesor excelente y un temario muy bueno. También me han gustado mucho las entrevistas y los recorridos por las páginas web que tienen recomendadores.

By 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.

By Pawel S

Dec 11, 2016

As a software engineer with computer science background I found that course enhancing my knowledge. I'm going to continue the specialization.

By 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

By tao L

Jul 22, 2018

I think I am on the right track to changing my career from java engineer from data scientist, this course is one of the best start point

By Francisco C

Mar 21, 2017

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

By Abhijith R

Aug 30, 2020

Great intro to recommendation systems, the course is well structured and engaging to all students of different backgrounds.

By Тефикова А Р

Oct 05, 2016

Курс очень понравился, спасибо большое за такую уникальную возможность вникнуть в суть рекомендательных систем!

By Arif L

Jun 14, 2020

I am confused using Java for programming, it is better using python or R in the next course

By Patrick D

Jun 25, 2017

Great, thorough introduction with tracks for both Java programmers and non-programmers.

By Kevin R

Oct 09, 2017

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

By Ashwin R

Jun 26, 2017

An excellent in-depth introduction into the concepts around recommendation systems!

By Xinzhi Z

Jul 18, 2019

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

By shayue

Apr 11, 2019

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