Clustering (Kmeans Vs. Gaussian Mixture Models) Lecture

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Carleton Artificial Intelligence Society (CAIS)

Clustering (Kmeans Vs. Gaussian Mixture Models) Lecture

In this lecture, we will introduce clustering as an unsupervised learning task. We will study in detail the Kmeans clustering algorithm, one of the most popular clustering approaches. Then, we will present a more generalized method for estimating the parameters of underlying distributions in the data, Gaussian Mixture Model (GMM). Finally, we will demonstrate how we can apply the Expectation-Maximization (EM) algorithm to estimate the parameters of GMM.

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Date And Time

Wednesday, November 18, 2020 06:00 PM to
08:00 PM
 

Location

Online Event
 

Venue

MS Teams Live
 

Event Types

Workshops
 

Event Category

Lectures

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