Полный видеокурс по искусственному интеллекту CS221 от университета Stanford (2019)

[GuDron]

Полный курс по искусственному интеллекту CS221 от университета Stanford
Stanford CS221: Artificial Intelligence: Principles and Techniques | Autumn 2019

Lecture 1: Overview
Lecture 2: Machine Learning 1 - Linear Classifiers, SGD
Lecture 3: Machine Learning 2 - Features, Neural Networks
Lecture 4: Machine Learning 3 - Generalization, K-means
Lecture 5: Search 1 - Dynamic Programming, Uniform Cost Search
Lecture 6: Search 2 - A*
Lecture 7: Markov Decision Processes - Value Iteration
Lecture 8: Markov Decision Processes - Reinforcement Learning
Lecture 9: Game Playing 1 - Minimax, Alpha-beta Pruning
Lecture 10: Game Playing 2 - TD Learning, Game Theory
Lecture 11: Factor Graphs 1 - Constraint Satisfaction Problems
Lecture 12: Factor Graphs 2 - Conditional Independence
Lecture 13: Bayesian Networks 1 - Inference
Lecture 14: Bayesian Networks 2 - Forward-Backward
Lecture 15: Bayesian Networks 3 - Maximum Likelihood
Lecture 16: Logic 1 - Propositional Logic
Lecture 17: Logic 2 - First-order Logic
Lecture 18: Deep Learning
Lecture 19: Conclusion