Udemy - Artificial Intelligence Reinforcement Learning in Python

Files:

• 1. Introduction and outline.mp4 (10.1 MB)
• 1. Introduction and outline.vtt (12.0 KB)
• 2. What is Reinforcement Learning.mp4 (22.0 MB)
• 2. What is Reinforcement Learning.vtt (24.0 KB)
• 3. Where to get the Code.mp4 (4.5 MB)
• 3. Where to get the Code.vtt (4.9 KB)
• 4. Strategy for Passing the Course.mp4 (9.5 MB)
• 4. Strategy for Passing the Course.vtt (10.7 KB)

• 1. Problem Setup and The Explore-Exploit Dilemma.mp4 (6.5 MB)
• 1. Problem Setup and The Explore-Exploit Dilemma.vtt (7.1 KB)
• 2. Epsilon-Greedy.mp4 (2.8 MB)
• 2. Epsilon-Greedy.vtt (2.9 KB)
• 3. Updating a Sample Mean.mp4 (2.2 MB)
• 3. Updating a Sample Mean.vtt (2.0 KB)
• 4. Comparing Different Epsilons.mp4 (8.0 MB)
• 4. Comparing Different Epsilons.vtt (4.9 KB)
• 5. Optimistic Initial Values.mp4 (5.1 MB)
• 5. Optimistic Initial Values.vtt (3.0 KB)
• 6. UCB1.mp4 (8.2 MB)
• 6. UCB1.vtt (7.4 KB)
• 7. Bayesian Thompson Sampling.mp4 (51.8 MB)
• 7. Bayesian Thompson Sampling.vtt (11.0 KB)
• 8. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4 (10.6 MB)
• 8. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.vtt (5.5 KB)
• 9. Nonstationary Bandits.mp4 (7.5 MB)
• 9. Nonstationary Bandits.vtt (7.1 KB)

• 1. Naive Solution to Tic-Tac-Toe.mp4 (6.1 MB)
• 1. Naive Solution to Tic-Tac-Toe.vtt (6.6 KB)
• 10. Tic Tac Toe Code Main Loop and Demo.mp4 (9.4 MB)
• 10. Tic Tac Toe Code Main Loop and Demo.vtt (8.4 KB)
• 11. Tic Tac Toe Summary.mp4 (8.3 MB)
• 11. Tic Tac Toe Summary.vtt (9.3 KB)
• 2. Components of a Reinforcement Learning System.mp4 (12.7 MB)
• 2. Components of a Reinforcement Learning System.vtt (13.4 KB)
• 3. Notes on Assigning Rewards.mp4 (4.2 MB)
• 3. Notes on Assigning Rewards.vtt (4.5 KB)
• 4. The Value Function and Your First Reinforcement Learning Algorithm.mp4 (103.7 MB)
• 4. The Value Function and Your First Reinforcement Learning Algorithm.vtt (21.7 KB)
• 5. Tic Tac Toe Code Outline.mp4 (5.0 MB)
• 5. Tic Tac Toe Code Outline.vtt (5.9 KB)
• 6. Tic Tac Toe Code Representing States.mp4 (4.4 MB)
• 6. Tic Tac Toe Code Representing States.vtt (4.5 KB)
• 7. Tic Tac Toe Code Enumerating States Recursively.mp4 (9.8 MB)
• 7. Tic Tac Toe Code Enumerating States Recursively.vtt (10.3 KB)
• 8. Tic Tac Toe Code The Environment.mp4 (10.0 MB)
• 8. Tic Tac Toe Code The Environment.vtt (10.9 KB)
• 9. Tic Tac Toe Code The Agent.mp4 (9.0 MB)
• 9. Tic Tac Toe Code The Agent.vtt (10.0 KB)

• 1. Gridworld.mp4 (3.4 MB)
• 1. Gridworld.vtt (3.7 KB)
• 2. The Markov Property.mp4 (7.2 MB)
• 2. The Markov Property.vtt (7.7 KB)
• 3. Defining and Formalizing the MDP.mp4 (6.6 MB)
• 3. Defining and Formalizing the MDP.vtt (7.2 KB)
• 4. Future Rewards.mp4 (5.2 MB)
• 4. Future Rewards.vtt (5.5 KB)
• 5. Value Function Introduction.mp4 (19.7 MB)
• 5. Value Function Introduction.vtt (14.5 KB)
• 6. Value Functions.mp4 (8.3 MB)
• 6. Value Functions.vtt (11.0 KB)
• 7. Bellman Examples.mp4 (87.1 MB)
• 7. Bellman Examples.vtt (25.8 KB)
• 8. Optimal Policy and Optimal Value Function.mp4 (3.2 MB)
• 8. Optimal Policy and Optimal Value Function.vtt (4.7 KB)
• 9. MDP Summary.mp4 (2.4 MB)
• 9. MDP Summary.vtt (2.4 KB)

• 1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4 (4.8 MB)
• 1. Intro to Dynamic Programming and Iterative Policy Evaluation.vtt (4.9 KB)
• 10. Dynamic Programming Summary.mp4 (8.3 MB)
• 10. Dynamic Programming Summary.vtt (8.6 KB)
• 2. Gridworld in Code.mp4 (11.5 MB)
• 2. Gridworld in Code.vtt (10.0 KB)
• 3. Iterative Policy Evaluation in Code.mp4 (12.1 MB)
• 3. Iterative Policy Evaluation in Code.vtt (9.3 KB)
• 4. Policy Improvement.mp4 (4.5 MB)
• 4. Policy Improvement.vtt (4.7 KB)
• 5. Policy Iteration.mp4 (3.1 MB)
• 5. Policy Iteration.vtt (3.2 KB)
• 6. Policy Iteration in Code.mp4 (7.6 MB)
• 6. Policy Iteration in Code.vtt (5.6 KB)
• 7. Policy Iteration in Windy Gridworld.mp4 (9.1 MB)
• 7. Policy Iteration in Windy Gridworld.vtt (7.5 KB)
• 8. Value Iteration.mp4 (6.2 MB)
• 8. Value Iteration.vtt (6.4 KB)
• 9. Value Iteration in Code.mp4 (4.9 MB)
• 9. Value Iteration in Code.vtt (3.0 KB)

• 1. Monte Carlo Intro.mp4 (5.0 MB)
• 1. Monte Carlo Intro.vtt (5.4 KB)
• 2. Monte Carlo Policy Evaluation.mp4 (8.8 MB)
• 2. Monte Carlo Policy Evaluation.vtt (9.8 KB)
• 3. Monte Carlo Policy Evaluation in Code.mp4 (7.9 MB)
• 3. Monte Carlo Policy Evaluation in Code.vtt (5.6 KB)
• 4. Policy Evaluation in Windy Gridworld.mp4 (7.8 MB)
• 4. Policy Evaluation in Windy Gridworld.vtt (4.9 KB)
• 5. Monte Carlo Control.mp4 (9.3 MB)
• 5. Monte Carlo Control.vtt (9.3 KB)
• 6. Monte Carlo Control in Code.mp4 (10.2 MB)
• 6. Monte Carlo Control in Code.vtt (5.3 KB)
• 7. Monte Carlo Control without Exploring Starts.mp4 (4.6 MB)
• 7. Monte Carlo Control without Exploring Starts.vtt (5.0 KB)
• 8. Monte Carlo Control without Exploring Starts in Code.mp4 (8.1 MB)
• 8. Monte Carlo Control without Exploring Starts in Code.vtt (3.3 KB)
• 9. Monte Carlo Summary.mp4 (5.7 MB)
• 9. Monte Carlo Summary.vtt (6.5 KB)

• 1. Temporal Difference Intro.mp4 (2.7 MB)
• 1. Temporal Difference Intro.vtt (3.1 KB)
• 2. TD(0) Prediction.mp4 (5.8 MB)
• 2. TD(0) Prediction.vtt (5.8 KB)
• 3. TD(0) Prediction in Code.mp4 (5.3 MB)
• 3. TD(0) Prediction in Code.vtt (3.6 KB)
• 4. SARSA.mp4 (8.2 MB)
• 4. SARSA.vtt (8.9 KB)
• 5. SARSA in Code.mp4 (8.8 MB)
• 5. SARSA in Code.vtt (5.0 KB)
• 6. Q Learning.mp4 (4.8 MB)
• 6. Q Learning.vtt (5.4 KB)
• 7. Q Learning in Code.mp4 (5.4 MB)
• 7. Q Learning in Code.vtt (3.1 KB)
• 8. TD Summary.mp4 (3.9 MB)
• 8. TD Summary.vtt (4.3 KB)

• 1. Approximation Intro.mp4 (6.5 MB)
• 1. Approximation Intro.vtt (6.5 MB)
• 2. Linear Models for Reinforcement Learning.mp4 (6.5 MB)
• 2. Linear Models for Reinforcement Learning.vtt (6.8 KB)
• 3. Features.mp4 (6.3 MB)
• 3. Features.vtt (6.3 KB)
• 4. Monte Carlo Prediction with Approximation.mp4 (2.8 MB)
• 4. Monte Carlo Prediction with Approximation.vtt (2.2 KB)
• 5. Monte Carlo Prediction with Approximation in Code.mp4 (6.6 MB)
• 5. Monte Carlo Prediction with Approximation in Code.vtt (3.7 KB)
• 6. TD(0) Semi-Gradient Prediction.mp4 (8.3 MB)
• 6. TD(0) Semi-Gradient Prediction.vtt (5.8 KB)
• 7. Semi-Gradient SARSA.mp4 (4.7 MB)
• 7. Semi-Gradient SARSA.vtt (5.0 KB)
• 8. Semi-Gradient SARSA in Code.mp4 (10.6 MB)
• 8. Semi-Gradient SARSA in Code.vtt (4.9 KB)
• 9. Course Summary and Next Steps.mp4 (13.2 MB)
• 9. Course Summary and Next Steps.vtt (14.5 KB)

• 1. What is the Appendix.mp4 (5.5 MB)
• 1. What is the Appendix.vtt (3.4 KB)
• 10. What order should I take your courses in (part 1).mp4 (29.3 MB)
• 10. What order should I take your courses in (part 1).vtt (15.2 KB)
• 11. What order should I take your courses in (part 2).mp4 (37.6 MB)
• 11. What order should I take your courses in (part 2).vtt (22.3 KB)
• 12. Where to get discount coupons and FREE deep learning material.mp4 (4.0 MB)
• 12. Where to get discount coupons and FREE deep learning material.vtt (3.3 KB)
• 2. Windows-Focused Environment Setup 2018.mp4 (186.4 MB)
• 2. Windows-Focused Environment Setup 2018.vtt (18.9 KB)
• 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 (43.9 MB)
• 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt (16.6 KB)
• 4. How to Code by Yourself (part 1).mp4 (24.5 MB)
• 4. How to Code by Yourself (part 1).vtt (27.3 KB)
• 5. How to Code by Yourself (part 2).mp4 (14.8 MB)
• 5. How to Code by Yourself (part 2).vtt (16.7 KB)
• 6. How to Succeed in this Course (Long Version).mp4 (18.3 MB)
• 6. How to Succeed in this Course (Long Version).vtt (13.7 KB)
• 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 (39.0 MB)
• 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt (29.9 KB)
• 8. Proof that using Jupyter Notebook is the same as not using it.mp4 (78.3 MB)
• 8. Proof that using Jupyter Notebook is the same as not using it.vtt (13.2 KB)
• 9. Python 2 vs Python 3.mp4 (7.8 MB)
• 9. Python 2 vs Python 3.vtt (5.9 KB)

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