| 09 Appendix/068 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 | 43.92 MB |
| 03 Build an Intelligent Tic-Tac-Toe Agent/017 The Value Function and Your First Reinforcement Learning Algorithm.mp4 | 26.13 MB |
| 01 Introduction and Outline/002 What is Reinforcement Learning.mp4 | 21.94 MB |
| 02 Return of the Multi-Armed Bandit/011 Bayesian Thompson Sampling.mp4 | 15.23 MB |
| 08 Approximation Methods/067 Course Summary and Next Steps.mp4 | 13.24 MB |
| 03 Build an Intelligent Tic-Tac-Toe Agent/015 Components of a Reinforcement Learning System.mp4 | 12.71 MB |
| 05 Dynamic Programming/034 Iterative Policy Evaluation in Code.mp4 | 12.06 MB |
| 05 Dynamic Programming/033 Gridworld in Code.mp4 | 11.46 MB |
| 08 Approximation Methods/066 Semi-Gradient SARSA in Code.mp4 | 10.61 MB |
| 02 Return of the Multi-Armed Bandit/012 Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4 | 10.57 MB |
| 06 Monte Carlo/047 Monte Carlo Control in Code.mp4 | 10.17 MB |
| 01 Introduction and Outline/001 Introduction and outline.mp4 | 10.1 MB |
| 03 Build an Intelligent Tic-Tac-Toe Agent/021 Tic Tac Toe Code The Environment.mp4 | 10.05 MB |
| 03 Build an Intelligent Tic-Tac-Toe Agent/020 Tic Tac Toe Code Enumerating States Recursively.mp4 | 9.79 MB |
| 01 Introduction and Outline/004 Strategy for Passing the Course.mp4 | 9.47 MB |
| 03 Build an Intelligent Tic-Tac-Toe Agent/023 Tic Tac Toe Code Main Loop and Demo.mp4 | 9.44 MB |
| 06 Monte Carlo/046 Monte Carlo Control.mp4 | 9.26 MB |
| 05 Dynamic Programming/038 Policy Iteration in Windy Gridworld.mp4 | 9.1 MB |
| 03 Build an Intelligent Tic-Tac-Toe Agent/022 Tic Tac Toe Code The Agent.mp4 | 9.01 MB |
| 07 Temporal Difference Learning/055 SARSA in Code.mp4 | 8.82 MB |
| 06 Monte Carlo/043 Monte Carlo Policy Evaluation.mp4 | 8.75 MB |
| 08 Approximation Methods/064 TD0 Semi-Gradient Prediction.mp4 | 8.35 MB |
| 05 Dynamic Programming/041 Dynamic Programming Summary.mp4 | 8.31 MB |
| 03 Build an Intelligent Tic-Tac-Toe Agent/024 Tic Tac Toe Summary.mp4 | 8.31 MB |
| 02 Return of the Multi-Armed Bandit/010 UCB1.mp4 | 8.23 MB |
| 07 Temporal Difference Learning/054 SARSA.mp4 | 8.2 MB |
| 06 Monte Carlo/049 Monte Carlo Control without Exploring Starts in Code.mp4 | 8.05 MB |
| 02 Return of the Multi-Armed Bandit/008 Comparing Different Epsilons.mp4 | 8.01 MB |
| 06 Monte Carlo/044 Monte Carlo Policy Evaluation in Code.mp4 | 7.91 MB |
| 06 Monte Carlo/045 Policy Evaluation in Windy Gridworld.mp4 | 7.81 MB |
| 05 Dynamic Programming/037 Policy Iteration in Code.mp4 | 7.62 MB |
| 02 Return of the Multi-Armed Bandit/013 Nonstationary Bandits.mp4 | 7.48 MB |
| 04 Markov Decision Proccesses/026 The Markov Property.mp4 | 7.18 MB |
| 04 Markov Decision Proccesses/029 Value Functions.mp4 | 7.08 MB |
| 04 Markov Decision Proccesses/027 Defining and Formalizing the MDP.mp4 | 6.64 MB |
| 08 Approximation Methods/063 Monte Carlo Prediction with Approximation in Code.mp4 | 6.56 MB |
| 02 Return of the Multi-Armed Bandit/005 Problem Setup and The Explore-Exploit Dilemma.mp4 | 6.47 MB |
| 08 Approximation Methods/060 Linear Models for Reinforcement Learning.mp4 | 6.46 MB |
| 08 Approximation Methods/059 Approximation Intro.mp4 | 6.46 MB |
| 04 Markov Decision Proccesses/030 Optimal Policy and Optimal Value Function.mp4 | 6.31 MB |
| 08 Approximation Methods/061 Features.mp4 | 6.24 MB |
| 05 Dynamic Programming/039 Value Iteration.mp4 | 6.18 MB |
| 03 Build an Intelligent Tic-Tac-Toe Agent/014 Naive Solution to Tic-Tac-Toe.mp4 | 6.11 MB |
| 07 Temporal Difference Learning/052 TD0 Prediction.mp4 | 5.82 MB |
| 06 Monte Carlo/050 Monte Carlo Summary.mp4 | 5.71 MB |
| 07 Temporal Difference Learning/057 Q Learning in Code.mp4 | 5.42 MB |
| 07 Temporal Difference Learning/053 TD0 Prediction in Code.mp4 | 5.32 MB |
| 04 Markov Decision Proccesses/028 Future Rewards.mp4 | 5.17 MB |
| 02 Return of the Multi-Armed Bandit/009 Optimistic Initial Values.mp4 | 5.12 MB |
| 03 Build an Intelligent Tic-Tac-Toe Agent/018 Tic Tac Toe Code Outline.mp4 | 5.03 MB |