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Lecture - 27 Learning : Neural Networks
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Classroom Contents
Artificial Intelligence
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- 1 Lecture - 1 Introduction
- 2 Lecture - 2 Problem Solving by Search
- 3 Lecture - 3 Searching with Costs
- 4 Lecture - 4 Informed State Space Search
- 5 Lecture - 5 Heuristic Search: A* and Beyond
- 6 Lecture - 6 Problem Reduction Search: AND/OR Graphs
- 7 Lecture - 7 Searching Game Trees
- 8 Lecture - 8 Knowledge Based Systems: Logic and Deduction
- 9 Lecture - 9 First Order Logic
- 10 Lecture - 10 Inference in First Order Logic
- 11 Lecture - 11 Resolution - Refutation Proofs
- 12 Lecture - 12 Resolution Refutation Proofs
- 13 Lecture - 13 Logic Programming : Prolog
- 14 Lecture - 14 Prolog Programming
- 15 Lecture - 15 Prolog: Exercising Control
- 16 Lecture - 16 Additional Topics
- 17 Lecture - 17 Introduction to Planning
- 18 Lecture - 18 Partial Order Planning
- 19 Lecture - 19 GraphPLAN and SATPlan
- 20 Lecture - 20 SATPlan
- 21 Lecture - 21 Reasoning Under Uncertainity
- 22 Lecture - 22 Bayesian Networks
- 23 Lecture - 23 Reasoning with Bayes Networks
- 24 Lecture - 24 Reasoning with Bayes networks (Contd.)
- 25 Lecture - 25 Reasoning Under Uncertainity: Issues
- 26 Lecture - 26 Learning : Decision Trees
- 27 Lecture - 27 Learning : Neural Networks
- 28 Lecture - 28 Back Propagation Learning
