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lectures

This is an old revision of the document!

Lectures

The Lectures for this course include:

Lecture 1 - course introduction and fuzzy logic
Lecture 2 - preliminaries and fuzzy logic
- Alternative Lecture 2 - Rough Sets in KDD: Tutorial Notes
Lecture 3 - finish fuzzy logic and begin rough sets
- fuzzy logic cases
Lecture 4 - more roughsets
Lecture 5 - more roughsets-Various Reducts & Rough Sets Applications
Lecture 6 - Neural Networks
Lecture 7 - More on Neural Networks
Lecture 8 - Evolutionary Computing: What
Lecture 9 - Genetic Algorithms & Evolution Strategies
Lecture 10 - Evolutionary & Genetic Programming
Lecture 11 - Probabilistic Reasoning: Why
Lecture 12 - Bayesian Networks
Lecture 13 - Discussion on Bayesian Networks
Lecture 14 - Recurrent Neural Networks
|Lecture 15 - Web Intelligence, Brain Informatics and Granular Computing
Lecture 15a - Web Intelligence meet Brain Informatics
Lecture 16 - Granular Computing
Lecture 16a - Zadeh's Granular Computing
Lecture 16 - Erich's Granular Computing

lectures.1299150593.txt.gz · Last modified: 2011/03/03 11:09 by nick

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