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Avis et commentaires pour l'étudiant pour Nearest Neighbor Collaborative Filtering par Université du Minnesota

4.3
211 notes
49 avis

À propos du cours

In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. You will explore and implement variations of the user-user algorithm, and will explore the benefits and drawbacks of the general approach. Then you will learn the widely-practiced item-item collaborative filtering algorithm, which identifies global product associations from user ratings, but uses these product associations to provide personalized recommendations based on a user's own product ratings....

Meilleurs avis

SS

Mar 31, 2019

Thank you so very much to open my eye see more view of recommendation field not only algorithms but use case and many trouble-shooting in worldwide business, moreover interview with noble professor.

NR

Feb 04, 2018

Extremely informative course! It would be great if the assignments are created on python or R in the next season's offering. Thanks for the knowledge!

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1 - 25 sur 49 Examens pour Nearest Neighbor Collaborative Filtering

par LU W

Sep 01, 2018

It would be better to provide other programming language such as python in honour assignment. And in the assignment should more emphasis on the algorithm not rely on too much others such as Lenskit.

par LAURENT B

Feb 05, 2018

There is an error in the assignment week 4 : the spreadsheet normalize by user instead of by item

par karthik n

Aug 10, 2018

(+) The course material is good with real world examples and interviews with different people.

(+) Interesting material

(-) The assignments had mistakes.

(-) There is no example provided for practice before jumping into assignments.

par Jack B

Oct 24, 2017

The course is less helpful than the others in the specialty. The lecture should include an example to help clarify the understanding necessary for Quiz Part II and Part IV. The instructors didn't respond to the many questions in Week 4 forum and I was unable to complete the course.

par Domenico P

Nov 20, 2017

Some exercises have wrong directions !!!

par Srikanth K S

Jan 05, 2017

instructions for assignments are not clear! Lectures are good, but its practically impossible to get the certificate.

par Sorratat S

Mar 31, 2019

Thank you so very much to open my eye see more view of recommendation field not only algorithms but use case and many trouble-shooting in worldwide business, moreover interview with noble professor.

par srikalyan

Jun 13, 2017

Very good assignments, honors track.

par Nicolau L W

Sep 02, 2017

Great course, nice theory and interesting exercise with the sheets and making actual Java programs to implement the algorithms. I would love to see some more in-depth probability theory, and considerations about when the algorithms deviate from the theory, or connections to other theories, but I suppose the course is more accessible and interesting like this. The interviews are probably my favorite part!

par Apurva D

Aug 03, 2017

Loved it...many thanks Prof. Joe for bringing this content to Coursera

par Pawel S

Jan 08, 2017

I love it. Would be cool to be able download all materials in one big .zip file (e.g for searching using grep) ;-)

par Dan S R

Jun 15, 2017

Very satisfied to do this, the videos are too long, very good quality and a lot of practical information.

I love it!

par Hossein E

Dec 13, 2017

everything best. But technical support in Forum and when a student needs help when he is learning in Vienna alone is the worst

thanks very much !

par Light0617

Jul 20, 2017

a great class, I learned some insight in these algorithms

par Ben C

Nov 17, 2017

Exercises take time but really helpful.

par Ashwin R

Aug 04, 2017

Awesome as always, Joe and Michael rock. The interview with Brad Miller was stellar, felt like listening to the legends of rock-n-roll!

par Christian J

Jul 17, 2017

Very good course, there is a glaring error in Week 4s assignment. But if you check the forums it can be easily solved

par Sanjay K

Jan 17, 2018

Provides a good overview of item based and user based collaborative filtering approaches.

par naveen r

Feb 04, 2018

Extremely informative course! It would be great if the assignments are created on python or R in the next season's offering. Thanks for the knowledge!

par Seema P

Feb 14, 2017

Awesome Professors!Great Material.Very thankful to Coursera for providing this course.

par Keshaw S

Feb 13, 2018

All in all, it is a comprehensive introduction to collaborative filtering. It allows the reader which paradigms and what tools to use in specific situations. I still have some complains with the excel assignments though.

par Twinkle

Apr 30, 2018

very nice

par XIN X

Oct 23, 2017

in-depth and well-made to follow

par Hagay L

Jul 08, 2019

Great learning experience about collaborative filtering!

par Xinzhi Z

Jul 23, 2019

Nice course!