Chevron Left
Volver a Introduction to Recommender Systems: Non-Personalized and Content-Based

Opiniones y comentarios de aprendices correspondientes a Introduction to Recommender Systems: Non-Personalized and Content-Based por parte de Universidad de Minnesota

607 calificaciones
128 reseña

Acerca del 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....

Principales reseñas


12 de feb. 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 dic. 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).

Filtrar por:

51 - 75 de 126 revisiones para 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 oct. 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 oct. 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 feb. 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 oct. 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

7 de nov. de 2016

pues esta bien chido el curso

por Mai H S

19 de ene. de 2019

good exercises & lectures


17 de sep. de 2020

Wonderful experience

por Julia E

8 de nov. de 2017

Thank you very much!

por Zhaoqi W

12 de may. de 2022

Easy to understand.

por sagar s

4 de oct. de 2018

Awesome. Worth it!