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01 Introduction and Outline/001 Introduction and outline.mp4
10.1MB
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01 Introduction and Outline/002 What is Reinforcement Learning.mp4
21.94MB
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01 Introduction and Outline/003 Where to get the Code.mp4
4.45MB
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01 Introduction and Outline/004 Strategy for Passing the Course.mp4
9.47MB
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02 Return of the Multi-Armed Bandit/005 Problem Setup and The Explore-Exploit Dilemma.mp4
6.47MB
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02 Return of the Multi-Armed Bandit/006 Epsilon-Greedy.mp4
2.78MB
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02 Return of the Multi-Armed Bandit/007 Updating a Sample Mean.mp4
2.17MB
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02 Return of the Multi-Armed Bandit/008 Comparing Different Epsilons.mp4
8.01MB
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02 Return of the Multi-Armed Bandit/009 Optimistic Initial Values.mp4
5.12MB
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02 Return of the Multi-Armed Bandit/010 UCB1.mp4
8.23MB
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02 Return of the Multi-Armed Bandit/011 Bayesian Thompson Sampling.mp4
15.23MB
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02 Return of the Multi-Armed Bandit/012 Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4
10.57MB
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02 Return of the Multi-Armed Bandit/013 Nonstationary Bandits.mp4
7.48MB
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03 Build an Intelligent Tic-Tac-Toe Agent/014 Naive Solution to Tic-Tac-Toe.mp4
6.11MB
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03 Build an Intelligent Tic-Tac-Toe Agent/015 Components of a Reinforcement Learning System.mp4
12.71MB
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03 Build an Intelligent Tic-Tac-Toe Agent/016 Notes on Assigning Rewards.mp4
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03 Build an Intelligent Tic-Tac-Toe Agent/017 The Value Function and Your First Reinforcement Learning Algorithm.mp4
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03 Build an Intelligent Tic-Tac-Toe Agent/018 Tic Tac Toe Code Outline.mp4
5.03MB
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03 Build an Intelligent Tic-Tac-Toe Agent/019 Tic Tac Toe Code Representing States.mp4
4.42MB
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03 Build an Intelligent Tic-Tac-Toe Agent/020 Tic Tac Toe Code Enumerating States Recursively.mp4
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03 Build an Intelligent Tic-Tac-Toe Agent/021 Tic Tac Toe Code The Environment.mp4
10.05MB
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03 Build an Intelligent Tic-Tac-Toe Agent/022 Tic Tac Toe Code The Agent.mp4
9.01MB
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03 Build an Intelligent Tic-Tac-Toe Agent/023 Tic Tac Toe Code Main Loop and Demo.mp4
9.44MB
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03 Build an Intelligent Tic-Tac-Toe Agent/024 Tic Tac Toe Summary.mp4
8.31MB
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04 Markov Decision Proccesses/025 Gridworld.mp4
3.36MB
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04 Markov Decision Proccesses/026 The Markov Property.mp4
7.18MB
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04 Markov Decision Proccesses/027 Defining and Formalizing the MDP.mp4
6.64MB
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04 Markov Decision Proccesses/028 Future Rewards.mp4
5.17MB
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04 Markov Decision Proccesses/029 Value Functions.mp4
7.08MB
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04 Markov Decision Proccesses/030 Optimal Policy and Optimal Value Function.mp4
6.31MB
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04 Markov Decision Proccesses/031 MDP Summary.mp4
2.41MB
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05 Dynamic Programming/032 Intro to Dynamic Programming and Iterative Policy Evaluation.mp4
4.83MB
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05 Dynamic Programming/033 Gridworld in Code.mp4
11.46MB
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05 Dynamic Programming/034 Iterative Policy Evaluation in Code.mp4
12.06MB
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05 Dynamic Programming/035 Policy Improvement.mp4
4.53MB
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05 Dynamic Programming/036 Policy Iteration.mp4
3.13MB
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05 Dynamic Programming/037 Policy Iteration in Code.mp4
7.62MB
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05 Dynamic Programming/038 Policy Iteration in Windy Gridworld.mp4
9.1MB
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05 Dynamic Programming/039 Value Iteration.mp4
6.18MB
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05 Dynamic Programming/040 Value Iteration in Code.mp4
4.89MB
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05 Dynamic Programming/041 Dynamic Programming Summary.mp4
8.31MB
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06 Monte Carlo/042 Monte Carlo Intro.mp4
4.97MB
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06 Monte Carlo/043 Monte Carlo Policy Evaluation.mp4
8.75MB
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06 Monte Carlo/044 Monte Carlo Policy Evaluation in Code.mp4
7.91MB
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06 Monte Carlo/045 Policy Evaluation in Windy Gridworld.mp4
7.81MB
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06 Monte Carlo/046 Monte Carlo Control.mp4
9.26MB
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06 Monte Carlo/047 Monte Carlo Control in Code.mp4
10.17MB
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06 Monte Carlo/048 Monte Carlo Control without Exploring Starts.mp4
4.62MB
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06 Monte Carlo/049 Monte Carlo Control without Exploring Starts in Code.mp4
8.05MB
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06 Monte Carlo/050 Monte Carlo Summary.mp4
5.71MB
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07 Temporal Difference Learning/051 Temporal Difference Intro.mp4
2.72MB
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07 Temporal Difference Learning/052 TD0 Prediction.mp4
5.82MB
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07 Temporal Difference Learning/053 TD0 Prediction in Code.mp4
5.32MB
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07 Temporal Difference Learning/054 SARSA.mp4
8.2MB
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07 Temporal Difference Learning/055 SARSA in Code.mp4
8.82MB
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07 Temporal Difference Learning/056 Q Learning.mp4
4.84MB
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07 Temporal Difference Learning/057 Q Learning in Code.mp4
5.42MB
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07 Temporal Difference Learning/058 TD Summary.mp4
3.94MB
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08 Approximation Methods/059 Approximation Intro.mp4
6.46MB
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08 Approximation Methods/060 Linear Models for Reinforcement Learning.mp4
6.46MB
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08 Approximation Methods/061 Features.mp4
6.24MB
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08 Approximation Methods/062 Monte Carlo Prediction with Approximation.mp4
2.84MB
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08 Approximation Methods/063 Monte Carlo Prediction with Approximation in Code.mp4
6.56MB
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08 Approximation Methods/064 TD0 Semi-Gradient Prediction.mp4
8.35MB
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08 Approximation Methods/065 Semi-Gradient SARSA.mp4
4.7MB
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08 Approximation Methods/066 Semi-Gradient SARSA in Code.mp4
10.61MB
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08 Approximation Methods/067 Course Summary and Next Steps.mp4
13.24MB
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09 Appendix/068 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4
43.92MB
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09 Appendix/069 How to Code by Yourself part 1.mp4
24.53MB
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09 Appendix/070 How to Code by Yourself part 2.mp4
14.8MB
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09 Appendix/071 Where to get discount coupons and FREE deep learning material.mp4
4.02MB
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[FreeCourseSite.com].txt
1.07KB
[FreeCourseSite.com].url
127B
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