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

4.5
459 notes
93 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

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.

IP

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.

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1 - 25 sur 89 Examens pour Introduction to Recommender Systems: Non-Personalized and Content-Based

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 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 Nicolás A

Jun 28, 2018

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

par Mai H S

Jan 20, 2019

good exercises & lectures

par Mustafa S

Feb 08, 2019

Great course

par shayue

Apr 11, 2019

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

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 Garvit G

Mar 22, 2018

awesome course.

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 HN M

Aug 28, 2017

great!

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 Apurva D

Aug 03, 2017

Awesome content...loved the industry expert interviews....

par Тефикова А Р

Oct 05, 2016

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

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 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 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 Shuang L

Nov 21, 2017

great professors and inspiring lectures!

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 Luis D F

Apr 17, 2017

Really good course to get started with recommendation systems!

par Patrick D

Jun 25, 2017

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

par S A

Jun 30, 2017

Excellent course taught in simple language.

par Light0617

Jul 19, 2017

great!! Let me better understand the research and practical fields!

par Julia E

Nov 08, 2017

Thank you very much!

par 姚青桦

Oct 16, 2017

Pretty good

par Ashwin R

Jun 26, 2017

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