CO553: Introduction to Machine Learning | Department of Computing

This is an archived version of the course. Please see the latest version of the course.

Module 6

Unsupervised Learning

Introduction to Module 6
General concept of Clustering
The K-means algorithm
K-mean, hyper-parameter tuning, strengths and weaknesses
Probability density estimation
PDE - Non-parametric approaches
PDE - Parametric approaches
GMM-EM
GMM-EM - Hyper-parameter tuning
Quiz - Unsupervised Learning
Recording of Live Session

GMM-EM

For the last main part of this lecture, we will focus on the Gaussian Mixture Model (GMM) and the associated algorithm to fit it to the data: Expectation Maximisation (EM):

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