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Avis et commentaires pour d'étudiants pour Introduction to Recommender Systems: Non-Personalized and Content-Based par Université du Minnesota

541 évaluations
111 avis

À propos du cours

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....

Meilleurs avis


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.


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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1 - 25 sur 107 Avis pour Introduction to Recommender Systems: Non-Personalized and Content-Based

par Rashid K

Jan 02, 2018

well one thing I am struggling with programming in JAVA. Would not it be handy to have option to do assignment using languages like python/R? which are basically language of choice for data scientists and also easy to have grasp on for newbies. one more thing some time I just get stuck and felt like now way out. I did not get any answer/help form posts on the forum .

par Benjamin S S

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.

par Nicolás A

Jun 28, 2018

Too basic and too repetitive (the videos could be half as long)

par Tash B

Jun 27, 2018

Fantastic course. Lecturers have extensive experience in this field. Lectures include interviews with people who have successfully implemented recommender systems in their products or who are researching the permutations, challenges and extensions to recommender system development. Not only does the course provide the chance to build your own recommender systems (optional) but also highlights the complexities and opportunities for refining and improving recommendations. I highly recommend this course to anyone building recommendation systems.

par Seema P

Jan 07, 2017

Exceptional quality.The course content is comprehensive and practical enough applied at workplaces.

Guest lectures are super helpful and assignments are very practical yet make you think.

Thank you Coursera and Minnesota professors for this amazing course and wonderful opportunity for people like me with no background in recommendation systems learn the best research methods and practices in this field.

par 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

par 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.

par 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

par 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.

par 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.

par 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

par 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.

par 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.

par 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

par 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.

par 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).

par 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.

par 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.

par 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.

par 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.

par 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

par 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

par Francisco C

Mar 21, 2017

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

par Тефикова А Р

Oct 05, 2016

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

par Arif L

Jun 14, 2020

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