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Introduction to Recommender Systems: Non-Personalized and Content-Based に戻る

ミネソタ大学(University of Minnesota) による Introduction to Recommender Systems: Non-Personalized and Content-Based の受講者のレビューおよびフィードバック

4.5
601件の評価
125件のレビュー

コースについて

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....

人気のレビュー

BS
2019年2月12日

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
2017年12月7日

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).

フィルター:

Introduction to Recommender Systems: Non-Personalized and Content-Based: 26 - 50 / 123 レビュー

by Andrés C C

2021年8月7日

-​ Too slow, too much wandering around instead of focusing on the concepts - Outdated coding exercises that don't integrate properly with modern IDEs - Too much emphasis on spreadsheets, too little emphasis on coding - The coding exercises made in Java put too much emphasis on unrelated stuff, not just because of the language, but because of how they are prepared.

by Neha G

2019年11月20日

would give negative rating if it was possible, course appears non-cohesive and dispersed without any clear terminology being used in the videos. Assignments are not clear either.

by Francisco R

2020年7月7日

Info desactualizada y no tiene la opción de usar python

by Pham V H

2016年12月11日

the video is too long!

by Mehmet

2020年10月15日

Recommender systems have big impact in our digital life. In the past we trust acquaintance's opinions before buying, renting or watching. short time ago we handed over steering to the machines and algorithms. We trust their suggestions for watching, buying something, even driving a car. Therefore recommender systems will be top prior inevitable aspect for every organisation. This course is a brief introduction to Recommender System. I suggest everyone who interested in. Thank for Joseph Konstan and Michael Ekstrand

by Gurupratap S M

2019年12月1日

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

by Nesreen S

2019年11月14日

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.

by sidra n

2018年8月15日

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

2020年3月17日

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

2019年12月12日

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

2019年9月9日

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

2016年10月3日

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

2018年3月8日

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

2019年6月2日

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 Mario W

2021年7月3日

Great lecture with smaller exercises, fully met my expectations. Excellent lecturers with for me perfect understandable English, interesting interviews and wrap-ups. Congratulations and many thanks!

by Yuncheng W

2016年11月3日

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

2020年9月16日

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

2017年12月8日

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

2016年9月19日

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 R

2017年2月6日

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

2017年11月24日

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

2016年12月11日

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

2016年10月26日

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

2018年7月21日

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

2017年3月20日

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