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Cluster Analysis Unsupervised Machine Learning Course Bundle

Data science techniques for pattern recognition, data mining, k-means clustering, and hierarchical clustering etc.

Cluster Analysis is a statistical tool which is used to classify objects into groups called clusters, where the objects belonging to one cluster are more similar to the other objects in that same cluster and the objects of other clusters are completely different. In simple words cluster analysis divides data into clusters that are meaningful and useful. Clustering is used mainly for two purposes – clustering for understanding and clustering for utility.

What you’ll learn

Course Content

Requirements

Cluster Analysis is a statistical tool which is used to classify objects into groups called clusters, where the objects belonging to one cluster are more similar to the other objects in that same cluster and the objects of other clusters are completely different. In simple words cluster analysis divides data into clusters that are meaningful and useful. Clustering is used mainly for two purposes – clustering for understanding and clustering for utility.

Application of cluster analysis

Clustering Methods

Clustering methods can be divided into the following categories

Advantages of Cluster Analysis

Given below are the advantages of cluster analysis

Approaches to cluster analysis

There are a number of different approaches used to carry out cluster analysis which are divided into two

Cluster Analysis Course Objectives

At the end of this course you will be able to know