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Voltar para Nearest Neighbor Collaborative Filtering

Comentários e feedback de alunos de Nearest Neighbor Collaborative Filtering da instituição Universidade de MinnesotaUniversidade de Minnesota

4.3
193 classificações
44 avaliações

Sobre o curso

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....

Melhores avaliações

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 de {totalReviews} Avaliações para o Nearest Neighbor Collaborative Filtering

por 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.

por 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.

por LAURENT B

Feb 05, 2018

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

por Domenico P

Nov 20, 2017

Some exercises have wrong directions !!!

por 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.

por Srikanth K S

Jan 05, 2017

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

por Daniil

Jun 19, 2019

The course is pretty good, but the spreadsheet assignments are brutal: they are confusing, too tedious and don't have enough information to debug.

por Gui M T

Apr 01, 2019

Much better than the first course, covers more interesting algorithms in more depth. The assignments can be clearer instructions. I also wish the lectures cover actual mathematical examples to work us through the algorithms

por 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.

por Ankur S

Oct 16, 2018

Diverse content that helps in understanding the basic concepts of collaborative filtering. Interviews with people specializing in different nuances of collaborative filteering were very useful.

Some thoughts on what could be improved

Pace of narration. It can be faster

More exercises are needed to get more familiar with the concepts. Each lecture should have a exercise (not just a quiz)

por Daniil B

Jul 31, 2018

The course itself is interesting, but some of the programming assignments are horribly confusing, what makes you waste your time trying to decipher what the professor really meant. Spreadsheet assignment on Week 3 is the main reason I rate this course so low, and a lot of people on discussion forums agree with me on assignment quality

por Ankit A

Jun 21, 2018

Week 4 assignments can do with a bit more clarity.

por Jose R

May 27, 2018

Not clear examples in my opinion, and there was same complain made from several user and I never saw a reply and nothing was changed

por Twinkle

Apr 30, 2018

very nice

por Anyu S

Apr 29, 2018

Making honours programming exercise in Java is a mistake. Pls consider Python in the future. Assignment for week 4 uses formula differs from the course: wasted many hours that don't benefit learning.

por Alberto G

Mar 26, 2018

Assignments are not explained so well on this one

por Yury Z

Mar 22, 2018

The topics I am interested in covered by people who definitely has related expertise. But overall quality of the teaching materials expected to be higher. Forum is also a little bit deserted, although contains some critical hints to pass the assignments (such a hints worth to be included in the assignment descriptions itself). I want to support the course, and it is pity to give it only 4 of 5 stars, but I really expect more quality from the course I paid for.

por zhenyu z

Feb 21, 2018

the hands-on quiz is not well prepared.

por 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.

por 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!

por Andrew W

Jan 21, 2018

Thank you for this course -- it opened my eyes to the universal applicability of recommender systems in tech applications.

My feedback is that you could do more to tie the *implementation* to the theory and real-life applications you discuss. You have many great lectures talking about how these systems were implemented, qualitative differences, subtle differences, and interviewing people to give us perspectives. But then the videos on implementation (including working through the equations) are pretty sparse and short. I felt like I'm "on my own" to figure out how to go implement these in real life. The problem sets cover one test case, and that's it. I think you could update the lectures to focus more on different algorithms / equations in different scenarios, rather than just talking qualitatively about them.

Regardless thank you! I deeply appreciate this course and what you've done. I plan to help my Consulting clients directly based on what I learned from you.

por Sanjay K

Jan 17, 2018

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

por 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 !

por Daniel P

Dec 08, 2017

Rather non-technical, interesting general information, plus voluntary programming assignment which I personally found little bit "bulky". More effort I spent to get familiar with the library than to actually use the collaborative filtering algorithms.

por Dan T

Nov 24, 2017

I liked the course, assignment two for item item was so much harder than the user user piece. I really spent all my time fighting excel, rather that working on the problem. it would have been easier to program it in lenskit!