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Lecture Notes
(Last updated 26 Feb 2001)
Lecture 0 (Friday, January 12, 2001): A Brief Survey of Topics in Intelligent Systems Development
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Lecture 1 (Wednesday, January 17, 2001): Artificial Intelligence Topics Review
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Lecture 2 (Friday, January 19, 2001): Introduction to Machine Learning
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Lecture 3 (Monday, January 22, 2001): Data Mining Basics
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Lecture 4 (Wednesday, January 24, 2001): Version Spaces and the Candidate Elimination Algorithm
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Lecture 5 (Friday, January 26, 2001): Discussion (KDD 1 of 3) - From Data Mining to KDD
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Lecture 6 (Monday, January 29, 2001): Presentation (KDD 1 of 3) - From Data Mining to KDD
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Lecture 7 (Wednesday, January 31, 2001): Discussion (KDD 2 of 3) - Feature Selection for KDD
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Lecture 8 (Friday, February 2, 2001): Presentation (KDD 2 of 3) - Feature Selection for KDD
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Lecture 9 (Monday, February 5, 2001): Decision Trees and Inductive Bias
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Lecture 10 (Wednesday, February 7, 2001): Presentation (KDD 3 of 3) - Rule Induction
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Lecture 11 (Friday, February 9, 2001): Inductive Learning for KDD
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Lecture 12 (Monday, February 12, 2001): Perceptrons, Linear Separability, and The Perceptron Convergence Theorem
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Lecture 13 (Wednesday, February 14, 2001): Delta Rule (LMS / Widrow-Hoff) Learning and Winnow
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Lecture 14 (Friday, February 16, 2001): Overfitting Control and Backpropagation of Error
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Lecture 15 (Monday, February 19, 2001): Presentation (ANN 1 of 3) - Temporal Artificial Neural Networks
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Page created: 08 Jan 2001
Last updated: 18 Feb 2001
William H. Hsu
