Lectures on Machine Learning
Introduction I (
slides
)
Introduction II (
slides
)
Concept Learning (
slides
)
Decision-Tree Learning (
slides
)
Neural Networks (
slides
)
Evaluating Hypotheses (
slides
,
ROC slides
)
Bayesian Learning (
slides
)
Learning Theory (
slides
)
Kernel-based Methods (
slides
)
Instance-based Learning (
slides
)
Ensemble Methods (
slides
)
Genetic Algorithms (
slides
)
Learning Rule Sets (
slides
)
Graph-based Learning (
slides
) (
printer-friendly slides
)
Reinforcement Learning (
slides
)
Conclusions (
slides
)