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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

282 classificações
63 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

11 de Dez de 2019

i found this course very helpful and informative. it explains the theory while providing real-world examples on recommender systems. the assignment helps in clearing up any confusion with the material

30 de Mar de 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.

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1 — 25 de 63 Avaliações para o Nearest Neighbor Collaborative Filtering

por karthik n

10 de Ago de 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 Jack B

24 de Out de 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

5 de Jan de 2017

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

por Domenico P

20 de Nov de 2017

Some exercises have wrong directions !!!

por LU W

31 de Ago de 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 Laurent B

5 de Fev de 2018

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

por Daniel M

23 de Jun de 2019

The course material is good, but the course itself is merely okay due to some problems with the assignments that have gone unaddressed for years. The Item-Item filtering assignment solution does not match the formula given in the lectures, and the honors assignments use an outdated version of the code (at one point recommending a package that has been deprecated). Really needs some attention to fix bugs and update the software.

por Yonaton N H

22 de Set de 2019

There is good information in this course but there are so many problems in this course. There are major errors in the assignments and I was only about the get the right answers by reading the discussions on the message board. There are coding exercises but they expect you to write them in Java rather than a language used by data scientists such as Python or R. It is a good thing the made them optional.

por Akash S C

21 de Jul de 2019

good introduction to topics and algorithms but very little help provided for the assignment in clarifying doubts in forums and unclear explanations were given for assignments. also not providing option to use any other programming language like python or r to do programming assignment is a big miss. would still recommend this course to get started from basics about reco sys.

por Danill B

31 de Jul de 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 Anyu S

29 de Abr de 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 Daniil

19 de Jun de 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 Arun R

1 de Dez de 2019

THe item based assignment, parts II and IV didn't give enough guidance. Otherwise a decent course.

por Ankit A

21 de Jun de 2018

Week 4 assignments can do with a bit more clarity.

por Alberto G

26 de Mar de 2018

Assignments are not explained so well on this one

por Zhenyu Z

21 de Fev de 2018

the hands-on quiz is not well prepared.

por Kemal C K

7 de Mar de 2017

Lessons need more examples.

por Gregory R

19 de Abr de 2017

The content of the course is extremely useful, however assignments need review as the exercises results have mistakes and they are not explained very well (missing step by step guidance).

por Jose R

27 de Mai de 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 Konstantinos P

10 de Abr de 2017

Unfortunately, the content of the course is poor. Too many interviews and some of them are pointless.

por Alex B

25 de Ago de 2019

This course is taught at a really low level. Exercises are in spreadsheets which are more or less useless for practicing scale data applications. Spreadsheets contain information that makes importation into numerical processing software such as Pandas in Python or dplyr in R needlessly difficult and assumes the user can't even apply the distance formula.

Videos contain useful information but require wading through a lot of garbage at a slow pace, not useful for practitioners.

Assignments are poorly worded and some terminology is used questionably or flexibly (see the word "normalization"). Some assignments are so poorly done that there is an ongoing debate on the forums as to whether the autograder is messed up or the assignment instructions are messed up.

The "honors" track programming assignments use some piece of software with questionable generalizability. If I ever see lens kit in my own data work environment I will come back an edit my review but I find it unlikely. Furthermore, Java is not commonly used for data science or machine learning purposes making these assignments inaccessible to many users. Personally, I write in Java but I didn't find it fulfilling to waste my time playing "fill in the blanks" or "guess the library function" which is overall uninstructive.

Quiz assignments show true indications of the poor level of instruction. Recitation of pieces of information buried in 30 minutes videos that can be condensed into 5 are some of the finest examples of bad teaching. Regurgitating information found in required readings shows no level of comprehension of course material and is a severe disservice to students.

I will hope for better general coverage of recommender systems in the future in another course. Ideally using something applicable like Python, Scala (Spark), or even R.

por Deleted A

2 de Abr de 2020

Extremely subpar.

por Nicolau L W

2 de Set de 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!

por Ayoub B

23 de Set de 2020

I found this course very helpful and informative. it explains the theory while providing real-world examples on recommender systems. the assignment helps in clearing up any confusion with the material. Also, the Honors track assignments are very good, although I like using Java but would love to use Python instead.

por Keshaw S

13 de Fev de 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.