What you learn in Hierarchical Clustering ?

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Introduction to Hierarchical Clustering
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Agglomerative Hierarchical Clustering
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Euclidean Distance
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Manhattan Distance
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Minkowski Distance
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Jaccard Index

About this Course

Clustering is a very important part of machine learning that governs many applications that we have today. It is a concept that is widely used especially when we require the use of unsupervised learning techniques. Hierarchical clustering talks about how we could go on to pick up multiple data points and combine or separate them into individual clusters containing similar characteristics. Since it is very important for all you machine learning enthusiasts to understand this in detail, we here at Great Learning have come up with this course to help you get started with hierarchical clustering and to understand it completely.

 

Course Outline

Introduction to Hierarchical Clustering
Types of Hierarchical Clustering
Agglomerative Hierarchical Clustering
Euclidean and Manhattan Distance
Minkowski Distance and Jaccard Index
Cosine Similarity
Optimal Number of Clusters
Hierarchical Clustering Summary

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Hierarchical Clustering

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1.0 Hours

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