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Stanford CS221 Artificial Intelligence – Complete AI Foundations Course
Bayesian Networks 3 - Maximum Likelihood | Stanford CS221: AI (Autumn 2019)

Bayesian Networks 3 - Maximum Likelihood | Stanford CS221: AI (Autumn 2019)

Stanford CS221 Artificial Intelligence – Complete AI Foundations Course

الدرس السابق الدرس التالي

محتوى الكورس

جميع الدروس
19 درس
27:26 Overview Artificial Intelligence Course | Stanford CS221: Learn AI (Autumn 2019)
20:34 Machine Learning 1 - Linear Classifiers, SGD | Stanford CS221: AI (Autumn 2019)
22:23 Machine Learning 2 - Features, Neural Networks | Stanford CS221: AI (Autumn 2019)
23:07 Machine Learning 3 - Generalization, K-means | Stanford CS221: AI (Autumn 2019)
20:25 Search 1 - Dynamic Programming, Uniform Cost Search | Stanford CS221: AI (Autumn 2019)
21:54 Search 2 - A* | Stanford CS221: Artificial Intelligence (Autumn 2019)
23:07 Markov Decision Processes 1 - Value Iteration | Stanford CS221: AI (Autumn 2019)
14:38 Markov Decision Processes 2 - Reinforcement Learning | Stanford CS221: AI (Autumn 2019)
21:33 Game Playing 1 - Minimax, Alpha-beta Pruning | Stanford CS221: AI (Autumn 2019)
19:26 Game Playing 2 - TD Learning, Game Theory | Stanford CS221: Artificial Intelligence (Autumn 2019)
21:17 Factor Graphs 1 - Constraint Satisfaction Problems | Stanford CS221: AI (Autumn 2019)
17:51 Factor Graphs 2 - Conditional Independence | Stanford CS221: AI (Autumn 2019)
21:39 Bayesian Networks 1 - Inference | Stanford CS221: AI (Autumn 2019)
11:49 Bayesian Networks 2 - Forward-Backward | Stanford CS221: AI (Autumn 2019)
23:45 Bayesian Networks 3 - Maximum Likelihood | Stanford CS221: AI (Autumn 2019)
18:34 Logic 1 - Propositional Logic | Stanford CS221: AI (Autumn 2019)
19:55 Logic 2 - First-order Logic | Stanford CS221: AI (Autumn 2019)
12:57 Deep Learning | Stanford CS221: AI (Autumn 2019)
01:48 Conclusion | Stanford CS221: AI (Autumn 2019)