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In this video on Gaussian Mixture Model,we will explain the Gaussian mixture model in machine learning. We will also see the key components of GMM. After that, we will present you with realworld examples of GMM. A Gaussian Mixture Model (GMM) is a probabilistic model representing data as a mixture of multiple Gaussian distributions. It is called a mixture modelbecause it assumes that the data points are generated from a mix of Gaussian distributions, each associated with a certain probability.

00:00 Gaussian Mixture model
01:42 What is Gaussian Mixture Model?
02:31 Key components of a Gaussian Mixture Model
04:31 Realworld examples where Gaussian mixture models can be used
06:52 Demo

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