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Avis et commentaires pour d'étudiants pour Partitionnement de données par Université de l'Illinois à Urbana-Champaign

393 évaluations

À propos du cours

Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications....

Meilleurs avis


17 déc. 2018

This was my favorite course in the whole specialization. Everything is explained very concisely and clearly making the subject matter very easy to understand.


6 nov. 2019

Good course for understanding the Cluster Analysis & Algorithms, instructor is very experienced and well explained, thanks

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51 - 62 sur 62 Avis pour Partitionnement de données

par Venuu M

11 avr. 2019

The course helped me a lot. I loved this course

par Yogesh S M

27 janv. 2017

Learnt More Here Than I Did At My College!!

par Red R

18 janv. 2022

T​here are still unclear lessons


21 févr. 2019

Nice. Good Course

par aditya p

15 févr. 2017

good course!

par prasanna k p

22 nov. 2019

it will be very helpful for understanding if any examples given with dummy data for cluster evaluation

par Aden G

15 oct. 2016

I am concerned about the last assignment of this course. And I cannot get any help from here.

par Su-hyun K

14 sept. 2021

Test is important, but sometimes it's hard to find answer, kind guidance should be provided

par Chow K M

3 avr. 2021

Okay as an introduction to key concepts. Lack of depth into the specific calculations.


11 nov. 2017

My analysis is that the assessments do not match the depth of what is explained.

par Logan V

27 juin 2020

needs examples


19 mai 2021

If I sealect an option in quiz it says either »√/× but not display correct option