Machine Learning Course 2007 - Lecture Notes



Week Date of the lecture Slides covered Content
1 September 18, 2007 Introduction / Lecture 1 Introduction
2 September 21, 2007 PPT / PDF Quick revision of Probability Theory
3 October 2, 2007 PPT / PDF Concept Learning
4 October 5, 2007 PPT / PDF The Chi-square test
5 October 9, 2007 PPT / PDF Decision Trees (a)
6 October 12, 2007 (PPT / PDF) (PPT / PDF) Decision Trees (b)
Information Theory Basics
7 October 16, 2007 1st set of papers to review Previous Lecture on IT
Discuss critical reviews
8 October 19, 2007 PPT / PDF Neural Networks (a)
9 October 23, 2007 Finish previous lecture Neural Networks (b)
10 October 26, 2007 PPT / PDF Evaluating Hypotheses
11 October 30, 2007 PPT / PDF Bayesian Learning
12 November 4, 2007 PPT / PDF Ted Pedersen's tutorial on Expectation-Maximization
13 November 9, 2007 Finish Bayesian Learning Bayesian Networks
14 November 13, 2007 PPT / PDF Instance-based learning
15 November 16, 2007 Projects / Slides This is going to be a lecture on the course projects
16 November 23, 2007 PPT / PDF Learning Sets of Rules
17 November 27, 2007 Finish previous lecture Learning Sets of Rules (b)
18 November 30, 2007 PPT / PDF A lightweight introduction to Information Retrieval.
19 December 4, 2007 PPT / PDF Support Vector Machines (a)
20 December 7, 2007 Finish previous slides Support Vector Machines (b)
21 December 11, 2007 PPT / PDF Clustering Techniques
22 December 14, 2007 PPT / PDF Introduction to Data Mining
23 December 18, 2007 - Discussion about projects


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