GMM-EM

This is an archived version of the course.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

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):

<< Previous Next >>