[GET] Cluster Analysis Unsupervised Machine Learning Course Bundle

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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.
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6.5 hours on-demand video

Description
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

Cluster analysis is used in many fields like machine learning, market research, pattern recognition, data analysis, information retrieval, image processing and data compression.

Cluster analysis can help the marketers to find out distinct groups of their customer base.

Cluster analysis is used in the field of biology to find out plant and animal taxonomies and categorize genes with similar characteristics

Cluster analysis is used in an earth observation database to group the houses in a city according to the house type, value and location.

Clustering can also be used to segment the documents on the web based on a specific criteria

In data mining, cluster analysis is used to gain in-depth understanding about the characteristics of data in each cluster.

Clustering Methods

Clustering methods can be divided into the following categories

Partitioning method

Hierarchical Method

Density based method

Grid Based Method

Model Based Method

Constraint Based Method


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