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Introduction to Stanford A.I. Courses

The following introduction to Stanford A.I. Courses were recorded during the Fall of 2019 CS229: Machine Learning

 

 

Video
Course
Speaker
EE364A – Convex Optimization I John Duchi
CS234 – Reinforcement Learning Emma Brunskill
CS221 – Artificial Intelligence: Principles and Techniques Reed Preisent
CS228 – Probabilistic Graphical Models / CS236 – Deep Generative Models Jeremy Song
CS230 – Deep Learning Kian Katanforoosh
CS182 – Ethics, Public Policy, and Technological Change Rob Reich
CS224N – Natural Language Processing with Deep Learning Abigail See
CS271/BIODS220/BIOMEDIN220 – Artificial Intelligence in Healthcare Serena Yeung
CS205L – Continuous Mathematical Methods with an Emphasis on Machine Learning Jane Wu
CS237B – Principles of Robot Autonomy II Jeanette Bogh
AA228/CS238/AA229/CS239 – Decision Making Under Uncertainty Robert Moss
CS348A – Computer Graphics: Geometric Modeling Leo Guibas
CS330 – Deep Multi-Task and Meta Learning Suraj Nair
CS229T/STATS231 – Statistical Learning Theory Leo Mehr
CS224W – Machine Learning with Graphs Michele Catasta
CS333 – Safe and Interactive Robotics Dylan Losey

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