Hierarchical Clustering in Python Part 2 of 2 | Distance Measures | Linkage Algorithm | Profiling

In this Playlist on Clustering we will discuss the two essential Clustering techniques along with Python & R Codes:
- Hierarchical Clustering
- K Means Clustering
Learning Objectives:
- Why Clustering?
- What is Clustering?
- How do we find Similar Groups (Homogeneous Groups) in Data
- Distance as a measure of Similarity / Dissimilarity
- Types of Distance Measures
---- Euclidean
---- Manhattan
---- Minkowski
---- Jaccard
---- Chebyshev
- Hierarchical Clustering Algorithm
---- Linkage Concepts
- Partitioning Clustering (K Means Algorithm)
- Why K Means is a Faster & Superior technique compared to Hierarchical
- Why K Means is based on Variance and not Distance Measure
- Finding Optimum Number of Clusters
- Scree Plot
- Cluster Profiling
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