### What is Unsupervised learning?

Identification of hidden patterns and associations from data is unsupervised learning.

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Identification of hidden patterns and associations from data is unsupervised learning.

Clustering is used to partition data set into N distinct groups/clusters. These groups are semantically coherent in nature

Exclusive Clustering, Probabilistic (Fuzzy) Clustering, Hierarchical Clustering, Model-based Clustering

Dimensionality reduction is the process of transforming a high-dimensional data set, into a more compact representation with fewer features.

Principal Component Analysis (PCA) is a dimension reduction technique.

Each observation is assigned to one and only one cluster.

Each observation is assigned to one or more clusters with a probability of belonging to each.

K-Means starts by selecting initial centroids for the k-clusters by randomly choosing k observations

This approach starts with all observations either belonging to their own cluster or all observations belonging to one large cluster

A Gaussian Mixture Model describes an underlying distribution that is composed of multiple individual Gaussian distributions

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