| Week 1 |
COMP9417 Course Introduction | PDF |
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Introduction to Machine Learning and Data Mining | PDF |
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Note on Exercises | PDF |
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Concept Learning | PDF |
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Note on Exercises | PDF |
| Week 2 |
| |
Decision Tree Learning | PDF |
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Note on Pruning Parameters | PDF |
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Note on Exercises | PDF |
| Week 3 |
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Rule Learning | PDF |
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Notes | PDF |
| Week 4 |
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Machine Learning for Numeric Prediction | PDF |
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Notes | PDF |
| Week 5 |
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Instance Based Learning | PDF |
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Genetic Algorithms | PDF |
| Week 6 |
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Note on Assessable Learning Objectives (Mid-session exam) | PDF |
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Reinforcement Learning (guest lecture) | PDF |
| Week 7 |
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Logic and Learning | PDF |
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Aleph files for Michalski's trains problem | files |
| Week 8 |
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Evaluating Hypotheses | PDF |
| Week 9 |
Bayesian Learning | PDF |
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| Week 10 |
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Computational Learning Theory | PDF |
| Week 11 |
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No Free Lunch, Bias-Variance & Ensembles | PDF |
| Week 12 |
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Support Vector Machines | PDF |
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Unsupervised Learning | PDF |
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Note on Assessable Learning Objectives (Final exam) | PDF |