Reinforcement Learning (Stanford)

•  Lecture 1 - Introduction (Stanford)
• Lecture 2 - Given a Model of the World (Stanford)
• Lecture 3 - Model-Free Policy Evaluation (Stanford)
•  Lecture 5 - Value Function Approximation (Stanford)
• Lecture 6 - CNNs and Deep Q Learning (Stanford)
• Lecture 7 - Imitation Learning (Stanford)
• Lecture 8 - Policy Gradient I (Stanford)
• Lecture 9 - Policy Gradient II (Stanford)
• Lecture 10 - Policy Gradient III & Review (Stanford)
• Lecture 11 - Fast Reinforcement Learning (Stanford)
• Lecture 12 - Fast Reinforcement Learning II (Stanford)
• Lecture 13 - Fast Reinforcement Learning III (Stanford)
• Lecture 14 - Batch Reinforcement Learning (Stanford)
•  Lecture 15 - Monte Carlo Tree Search (Stanford)