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Fundamentals of Artificial Intelligence [Introduction]
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Fundamentals of Artificial Intelligence
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- 1 Fundamentals of Artificial Intelligence [Introduction]
- 2 Lec 01: Introduction to AI
- 3 Lec 02: Problem Solving as State Space Search
- 4 Lec 03: Uniformed Search
- 5 Lec 04: Heuristic Search
- 6 Lec 05: Informed Search
- 7 Lec 06: Constraint Satisfaction Problems
- 8 Lec 07: Searching AND/OR Graphs
- 9 Lec 08: Game Playing
- 10 Lec 09: Minimax + Alpha-Beta
- 11 Lec 10: Introduction to Knowledge Representation
- 12 Lec 11: Propositional Logic
- 13 Lec 12: First Order Logic -I
- 14 Lec 13: First Order Logic -II
- 15 Lec 14: Inference in First Order Logic - I
- 16 Lec 15: Inference in FOL - II
- 17 Lec 16: Answer Extraction
- 18 Lec 17: Procedural Control of Reasoning
- 19 Lec 18: Reasoning under Uncertainty
- 20 Lec 19: Bayesian Network
- 21 Lec 20: Decision Network
- 22 Lec 21: Introduction to Planning
- 23 Lec 22: Plan Space Planning
- 24 Lec 23: Planning Graph and GraphPlan
- 25 Lec 24: Practical Planning and Acting
- 26 Lec 25: Sequential Decision Problems
- 27 Lec 26: Making Complex Decisions
- 28 Lec 27: Introduction to Machine Learning
- 29 Lec 28: Learning Decision Trees
- 30 Lec 29: Linear Regression
- 31 Lec 30: Support Vector Machines
- 32 Lec 31: Unsupervised Learning
- 33 Lec 32: Reinforcement Learning
- 34 Lec 33: Learning in Neural Networks
- 35 Lec 34: Deep Learning: A Brief Overview
