Artificial Intelligence – Sem 5 AIML
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Course Overview
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Artificial Intelligence
- Agent and Peas Description [Module-2]
- Types of Agent [Module-2]
- Learning Agent [Module-2]
- BFS Algorithm with solved Example [Module-3]
- DFS ( Depth First Search ) Algorithm with solved Example [Module-3]
- IDFS ( Iterative Depth First Search ) Algorithm with solved Example [Module-3]
- GBFS Solved Example [Module-3]
- A star Solved Example [Module-3]
- Hill Climbing [Module-3]
- Hill Climbing algorithm [Module-3]
- Genetic Algorithm [Module-3]
- Genetic Algorithm Max one Problem Solved Example [Module-3]
- Min Max Solved Example [Module-3]
- Alpha-Beta Pruning Solved Example [Module-3]
- Propositional Logic (PL) Introduction [Module-4]
- PL to CNF Conversion With Solved Example [Module-4]
- First-Order Logic (FOL) Solved Example [Module-4]
- Resolution Tree Sum Part #1 [Module-4]
- Resolution Tree Sum Part #2 [Module-4]
- Bayesian Belief Network [Module-5]
- Bayesian Network toothache and Cavity sum [Module-5]
- Partial Order Planning with Example [Module-6]
- Supervised and Unsupervised Learning (AI and SC) [Module-6]
- Ensemble learning [Module-6]
- Expert System [Module-6]
- Module 1 [Notes]
- Module 2 [Notes]
- Module 3 [Notes]
- Module 4 [Notes]
- Module 5 [Notes]
- Module 6 [Notes]
- AI IMP
- Module 1[IMP]
- Module 2[IMP]
- Module 3[IMP]
- Module 4[IMP]
- Module 5[IMP]
- Module 6[IMP]
