Astra

Lecture 1_ Overview _ Stanford CS221_ AI (Autumn 2019)

Lecture 2_ Machine Learning 1 - Linear Classifiers, SGD _ Stanford CS221_ AI (Autumn 2019)

Lecture 5 Search 1 Dynamic Programming Uniform Cost Search Stanford CS221 AI Autumn 2019

Lecture 6_ Search 2 - A_ _ Stanford CS221_ AI (Autumn 2019)

Lecture 7 Markov Decision Processes Value Iteration Stanford CS221 AI Autumn 2019

Lecture 8_ Markov Decision Processes - Reinforcement Learning _ Stanford CS221_ AI (Autumn 2019)

Lecture 9_ Game Playing 1 - Minimax, Alpha-beta Pruning _ Stanford CS221_ AI (Autumn 2019)

Lecture 10 Game Playing 2 TD Learning Game Theory Stanford CS221 AI Autumn 2019

Lecture 11_ Factor Graphs 1 - Constraint Satisfaction Problems _ Stanford CS221_ AI (Autumn 2019)

Lecture 12_ Factor Graphs 2 - Conditional Independence _ Stanford CS221_ AI (Autumn 2019)

Lecture 13_ Bayesian Networks 1 - Inference _ Stanford CS221_ AI (Autumn 2019)

Lecture 14_ Bayesian Networks 2 - Forward-Backward _ Stanford CS221_ AI (Autumn 2019)

Lecture 15 Bayesian Networks 3 Maximum Likelihood Stanford CS221 AI Autumn 2019

Lecture 16 Logic 1 Propositional Logic Stanford CS221 AI Autumn 2019

Lecture 17_ Logic 2 - First-order Logic _ Stanford CS221_ AI (Autumn 2019)

Lecture 18_ Deep Learning _ Stanford CS221_ AI (Autumn 2019)

Lecture 19_ Conclusion _ Stanford CS221_ AI (Autumn 2019)

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