CSCE 496/896 lecture slides
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Lectures 0 and 1:
Administrivia and Introduction
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Lecture 2:
Concept Learning and the General-to-Specific Ordering
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Lecture 3:
Computational Learning Theory
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Lecture 4:
Decision Trees
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Lecture 5:
Artificial Neural Networks
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Lecture 6:
Evaluating Hypotheses
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Lecture 7:
Combining Classifiers: Weighted Majority, Boosting, and Bagging
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Lecture 8:
Bayesian Learning
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Lecture 9:
Instance-Based Learning
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Lecture 10:
Reinforcement Learning
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