AI & ML Artificial Intelligence: A Fundamental Guide
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-Get a deeper knowledge about Artificial Intelligence with this course-Learn the various aspects of Artificial Intelligence and its use in our lives-Get a detailed learning about AI and understand how these technologies can help solve challenging problems.
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Course content
Artificial Intelligence: A Fundamental Guide
- 2. Reasoning: Goal Trees and Problem SolvingWatchDuration: 45:58 min
- 1. Introduction and ScopeWatchDuration: 47:19 min
- 3. Reasoning: Goal Trees and Rule-Based Expert SystemsWatchDuration: 49:56 min
- 4. Search: Depth-First; Hill Climbing; BeamWatchDuration: 48:42 min
- 5. Search: Optimal; Branch and Bound; A*WatchDuration: 48:37 min
- 6. Search: Games; Minimax; and Alpha-BetaWatchDuration: 48:17 min
- 7. Constraints: Interpreting Line DrawingsWatchDuration: 49:13 min
- 8. Constraints: Search; Domain ReductionWatchDuration: 45:24 min
- 9. Constraints: Visual Object RecognitionWatchDuration: 51:32 min
- 10. Introduction to Learning; Nearest NeighborsWatchDuration: 49:56 min
- 12a: Neural NetsWatchDuration: 50:43 min
- 12b: Deep Neural NetsWatchDuration: 49:06 min
- 13. Learning: Genetic AlgorithmsWatchDuration: 47:16 min
- 14. Learning: Sparse Spaces; PhonologyWatchDuration: 47:49 min
- 15. Learning: Near Misses; Felicity ConditionsWatchDuration: 46:54 min
- 16. Learning: Support Vector MachinesWatchDuration: 49:34 min
- 17. Learning: BoostingWatchDuration: 51:40 min
- 18. Representations: Classes; Trajectories; TransitionsWatchDuration: 48:58 min
- 19. Architectures: GPS; SOAR; Subsumption; Society of MindWatchDuration: 49:06 min
- 21. Probabilistic Inference IWatchDuration: 48:30 min
- 22. Probabilistic Inference IIWatchDuration: 48:46 min
- 23. Model Merging; Cross-Modal Coupling; Course SummaryWatchDuration: 49:31 min
- Mega-R1. Rule-Based SystemsWatchDuration: 46:58 min
- Mega-R2. Basic Search; Optimal SearchWatchDuration: 51:56 min
- Mega-R3. Games; Minimax; Alpha-BetaWatchDuration: 50:56 min
- Mega-R4. Neural NetsWatchDuration: 52:38 min
- Mega-R5. Support Vector MachinesWatchDuration: 49:53 min
- Mega-R6. BoostingWatchDuration: 49:55 min
- Mega-R7. Near Misses; Arch LearningWatchDuration: 33:05 min
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10. Introduction to Learning; Nearest Neighbors
,14. Learning: Sparse Spaces; Phonology
,7. Constraints: Interpreting Line Drawings
,18. Representations: Classes; Trajectories; Transitions
,6. Search: Games; Minimax; and Alpha-Beta
,12a: Neural Nets
,4. Search: Depth-First; Hill Climbing; Beam
,Mega-R7. Near Misses; Arch Learning
,9. Constraints: Visual Object Recognition
,17. Learning: Boosting
,19. Architectures: GPS; SOAR; Subsumption; Society of Mind
,3. Reasoning: Goal Trees and Rule-Based Expert Systems
,12b: Deep Neural Nets
,23. Model Merging; Cross-Modal Coupling; Course Summary
,Mega-R6. Boosting
,13. Learning: Genetic Algorithms
,Mega-R5. Support Vector Machines
,2. Reasoning: Goal Trees and Problem Solving
,8. Constraints: Search; Domain Reduction
,16. Learning: Support Vector Machines
,22. Probabilistic Inference II
,1. Introduction and Scope
,21. Probabilistic Inference I
,15. Learning: Near Misses; Felicity Conditions
,5. Search: Optimal; Branch and Bound; A*
,Mega-R3. Games; Minimax; Alpha-Beta
,Mega-R4. Neural Nets
,Mega-R1. Rule-Based Systems
,Mega-R2. Basic Search; Optimal Search
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