K-State CIS 830: Lecture Notes - Spring, 2003

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Lecture Notes

(Last updated 16 Jan 2002)

Lecture 0 : A Brief Overview of Knowledge Discovery in Databases

Lecture 1 : Artificial Intelligence : Foundations Overview

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Lecture 2 : Introduction to Machine Learning

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Lecture 3 : Data Mining Basics

Lecture 4 : Genetic Algorithms, Genetic Programming and Evolutionary Computing

Lecture 5 : Graphical Models Of Probability for Causual Reasoning

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Lecture 6 : Learning bayesian Networks from Data

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Lecture 7 : More Learning Bayesian Networks from Data

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Lecture 8: Multi-Layer perceptrons and Backpropagation of Error
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Lecture 9 : Temporal ANNs

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Lecture 10 : Temporal Graphical Models Survey

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Lecture 13 : Topics in Graphical Models and ANNs

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Lecture 14 : More Genetic Algorithms and Genetic Programming

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Lecture 15 : Genetic Programming Issues: Code Growth

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Lecture 26 : Time In Neural Networks, Presentation by Jan Miksatko

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Lecture 27 : Multi-Objective Genetic Algorithms

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Lecture 30: Discussion: Object-Oriented Bayesian Networks
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Lecture 31: Neurogenesis
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Lecture 32: Parallel Genetic Algorithms
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Lecture 33: Cantu-Paz Discusssion
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Lecture 36: Dynamic Bayesian Networks
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Lecture 38: Is the Hippocampus a Kalman Filter?
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Lecture 39: Object-Oriented Bayesian Networks
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Page created: 16 Jan 2002
Last updated: 23 Jan 2003
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