Week | Project | Topic | PDF Slides |
1 | | Introduction - Machine Learning | |
| Introduction - Weka | | |
2 | | Data Preprocessing | |
Project 1 presentations | | ||
3 | | Decision Trees (I) | |
| Decision Trees (II) | ||
4 | Project 2 presentations | | |
| Neural Networks (I) | ||
5 | | Neural Networks (II) | |
| Neural Networks (III) | ||
6 | Project 3 presentations | | |
| Evaluating Hypothesis (I) | ||
7 | | Evaluating Hypothesis (II) | |
Project 4 presentations | | ||
8 | | Bayesian Learning (I) | |
| Bayesian Learning (II) | ||
9 | | Bayesian Learning (III) - K2 algorithm | |
Project 5 presentations | | ||
10 | | Instance-based Learning | |
Project 6 presentations | | ||
11 | | Genetic Algorithms (I) | |
| Genetic Algorithms (II) | ||
12 | Project 7 presentations | | |
| Rule Learning (I) | ||
13 | | Rule Learning (II) | |
| Reinforcement Learning |
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Machine Learning Slides
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