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Voltar para Introduction to Recommender Systems: Non-Personalized and Content-Based

Comentários e feedback de alunos de Introduction to Recommender Systems: Non-Personalized and Content-Based da instituição Universidade de MinnesotaUniversidade de Minnesota

610 classificações

Sobre o curso

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....

Melhores avaliações


12 de fev de 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.


7 de dez de 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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51 — 75 de 128 Avaliações para o Introduction to Recommender Systems: Non-Personalized and Content-Based

por Abhijith R

30 de ago de 2020

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

por Тефикова А Р

5 de out de 2016

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

por Chris C

6 de jul de 2021

Excellent content, great structured frameworks to understand when / why to use different recommenders

por Patrick D

25 de jun de 2017

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

por Kevin R

8 de out de 2017

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

por Ashwin R

26 de jun de 2017

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

por Santiago F

1 de fev de 2021

Muy claro y de gran ayuda para los que se estén introduciendo en el tema.

por Xinzhi Z

17 de jul de 2019

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

por 王涛

10 de abr de 2019

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

por Light0617

18 de jul de 2017

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

por Sushmita B

7 de jun de 2020

The course is very good and the course instructor is excellent .

por Luis D F R

17 de abr de 2017

Really good course to get started with recommendation systems!

por Apurva D

3 de ago de 2017

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

por Dan T

31 de out de 2017

great overview of the breadth of material to get started

por Sreenath A

30 de jun de 2017

Excellent course taught in simple language.

por Biswa s

28 de mar de 2018

Good overview on the recommend-er system.

por Sherry L

21 de nov de 2017

great professors and inspiring lectures!

por 王嘉奕

6 de nov de 2019

Excellent course which helps me a lot.

por Su L

23 de ago de 2019

great course, learnt a lot, thanks!

por Fernando C C

7 de nov de 2016

pues esta bien chido el curso

por Son M

19 de jan de 2019

good exercises & lectures


17 de set de 2020

Wonderful experience

por Julia E

8 de nov de 2017

Thank you very much!

por Zhaoqi W

12 de mai de 2022

Easy to understand.

por sagar s

4 de out de 2018

Awesome. Worth it!