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This is an archived version of the course.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

Introduction to Module 6

Welcome to Module 6! After 5 lectures focusing on supervised learning algorithms, we continue our introduction to Machine Learning journey today by covering several algorithms for unsupervised learning. The slides are on Materials, in case you want to take your own notes.

This module is divided into 9 videos, and the first one starts here:

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