Artificial Intelligence
À propos du cours
This course provides a foundational understanding of the principles of artificial intelligence. It explores the modeling and algorithmic techniques used to build intelligent agents that can perceive, reason, and act in complex environments.
Contenu du cours
Artificial Intelligence by Stanford University
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Overview Artificial Intelligence Course | Stanford CS221: Learn AI (Autumn 2019)
01:27:25 -
Machine Learning 1 – Linear Classifiers, SGD | Stanford CS221: AI (Autumn 2019)
01:20:33 -
Machine Learning 2 – Features, Neural Networks | Stanford CS221: AI (Autumn 2019)
01:22:22 -
Machine Learning 3 – Generalization, K-means | Stanford CS221: AI (Autumn 2019)
01:23:07 -
Search 1 – Dynamic Programming, Uniform Cost Search | Stanford CS221: AI (Autumn 2019)
01:20:25 -
Search 2 – A* | Stanford CS221: Artificial Intelligence (Autumn 2019)
01:21:53 -
Markov Decision Processes 1 – Value Iteration | Stanford CS221: AI (Autumn 2019)
01:23:06 -
Markov Decision Processes 2 – Reinforcement Learning | Stanford CS221: AI (Autumn 2019)
01:14:38 -
Game Playing 1 – Minimax, Alpha-beta Pruning | Stanford CS221: AI (Autumn 2019)
01:21:33 -
Game Playing 2 – TD Learning, Game Theory | Stanford CS221: Artificial Intelligence (Autumn 2019)
01:19:25 -
Factor Graphs 1 – Constraint Satisfaction Problems | Stanford CS221: AI (Autumn 2019)
01:21:17 -
Factor Graphs 2 – Conditional Independence | Stanford CS221: AI (Autumn 2019)
01:17:50 -
Bayesian Networks 1 – Inference | Stanford CS221: AI (Autumn 2019)
01:21:39 -
Bayesian Networks 2 – Forward-Backward | Stanford CS221: AI (Autumn 2019)
01:11:49 -
Bayesian Networks 3 – Maximum Likelihood | Stanford CS221: AI (Autumn 2019)
01:23:45 -
Logic 1 – Propositional Logic | Stanford CS221: AI (Autumn 2019)
01:18:33 -
Logic 2 – First-order Logic | Stanford CS221: AI (Autumn 2019)
01:19:54 -
Deep Learning | Stanford CS221: AI (Autumn 2019)
01:12:56 -
Conclusion | Stanford CS221: AI (Autumn 2019)
01:01:48
Notes et avis de l’apprenant
Encore aucun avis !