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学生对 Coursera Project Network 提供的 Hierarchical Clustering: Customer Segmentation 的评价和反馈

4.3
82 个评分
17 条评论

课程概述

In this 1-hour long project-based course, you will learn how to use Python to implement a Hierarchical Clustering algorithm, which is also known as hierarchical cluster analysis. This type of algorithm groups objects of similar behavior into groups or clusters. The output of this model is a set of visualized clusters, where each cluster is distinct from each other cluster, and the objects within each cluster are broadly similar to each other in features. In this project, you will learn the fundamental theory and practical illustrations behind Hierarchical Clustering and learn to fit, examine, and utilize unsupervised Clustering models to examine relationships between unlabeled input features and output variables, using Python. We will walk you step-by-step into Machine Learning unsupervised problems. With every task in this project, you will expand your knowledge, develop new skills and broaden your experience in Machine Learning. Particularly, you will build a Hierarchical Clustering algorithm to apply market segmentation on a group of customers based on several features. By the end of this project, you will be able to build your own Hierarchical Clustering model and make amazing clusters of customers. In order to be successful in this project, you should just know the basics of Python and clustering algorithms....
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1 - Hierarchical Clustering: Customer Segmentation 的 17 个评论(共 17 个)

创建者 Uvnik G

May 19, 2020

This is a beginners level course. The instructor uses scipy and sklearn libraries without explaining them.

创建者 Pranay U

Apr 28, 2020

The project scope could have been expanded like adding other hierarchical clustering methods and then maybe differentiating it and then justifying which would be a better choice. However, this project basically highlights the application of hierarchical clustering using a dendrogram.

创建者 Chun

May 28, 2020

This course is unrealistically simplified and the project contains around 20 lines of codes in total.

创建者 MOHAMED M

Aug 17, 2020

That is a added vlue the profil, a trick to have in unsupervised learning. You would like the short just right of the work but the explaination is lack about libraries so it is to look about ;)

创建者 Badr k

May 14, 2020

Perfect Project. Thank You

创建者 Widhi A P

Jul 06, 2020

This is very good course

创建者 Asif A S A A M

Jul 11, 2020

amazing experience

创建者 SRAVAN K V

Jun 27, 2020

Very Good

创建者 Arvind K V

Jun 26, 2020

very easy

创建者 Rashmi M

Apr 21, 2020

very good

创建者 p s

Jun 26, 2020

Nice

创建者 tale p

Jun 17, 2020

good

创建者 Jack C

Jun 02, 2020

Good course, but the instructor was hard to understand and the quiz did not test your knowledge well. One reccomendation I would have is to add a coding assignment so that I know whether I understand the material.

创建者 Gnanasekaran

Sep 22, 2020

Excellent Project . But We Cant Understand Well by this videos ;)

创建者 Emily S M

Oct 14, 2020

Hi there, I must say that this project does not really have the depth that I would have like to receive with respects to clustering. The host did not talk about scaling each of the features, the choice of distance metric and what effect that has, and furthermore, what ward actually means, aside from minimising variance. In addition, there was not any information on understanding what the clusters actually mean - the fundamental problem in unsupervised learning. Perhaps I am asking too much from a beginner course but I am left with code, but little understanding.

创建者 orhan b

Aug 20, 2020

Unfortunately, the functions was not fully explained to student. Maybe it can be supported with more visual materials or can be repeated with different examples to understand difference. Questions were left on minds such as why we chose those parameters and what other options could be, what is the way we want to go more detailed analysis.

Moreover audio quality was bad and interface that used for coding is not handy for low resolution pc's.

创建者 Kiran K M

Jun 16, 2020

worst sound quality