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Please note that this page does not hosts or makes available any of the listed filenames. You
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| [CourseClub.Me].url |
48B |
| [DesireCourse.Net].url |
51B |
| [FreeCourseWorld.Com].url |
54B |
| 1. Approximation Intro.mp4 |
6.47MB |
| 1. Approximation Intro.srt |
7.99KB |
| 1. Gridworld.mp4 |
3.36MB |
| 1. Gridworld.srt |
4.04KB |
| 1. Introduction.mp4 |
34.24MB |
| 1. Introduction.srt |
4.17KB |
| 1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4 |
4.83MB |
| 1. Intro to Dynamic Programming and Iterative Policy Evaluation.srt |
5.37KB |
| 1. Monte Carlo Intro.mp4 |
4.97MB |
| 1. Monte Carlo Intro.srt |
5.96KB |
| 1. Naive Solution to Tic-Tac-Toe.mp4 |
6.12MB |
| 1. Naive Solution to Tic-Tac-Toe.srt |
7.21KB |
| 1. Problem Setup and The Explore-Exploit Dilemma.mp4 |
6.47MB |
| 1. Problem Setup and The Explore-Exploit Dilemma.srt |
7.80KB |
| 1. Stock Trading Project Section Introduction.mp4 |
26.77MB |
| 1. Stock Trading Project Section Introduction.srt |
6.84KB |
| 1. Temporal Difference Intro.mp4 |
2.73MB |
| 1. Temporal Difference Intro.srt |
3.33KB |
| 1. What is Reinforcement Learning.mp4 |
54.62MB |
| 1. What is Reinforcement Learning.srt |
10.92KB |
| 1. What is the Appendix.mp4 |
5.45MB |
| 1. What is the Appendix.srt |
3.72KB |
| 10. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4 |
10.57MB |
| 10. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.srt |
6.09KB |
| 10. Tic Tac Toe Code Main Loop and Demo.mp4 |
9.44MB |
| 10. Tic Tac Toe Code Main Loop and Demo.srt |
9.25KB |
| 10. Value Iteration in Code.mp4 |
4.89MB |
| 10. Value Iteration in Code.srt |
3.34KB |
| 10. What order should I take your courses in (part 1).mp4 |
29.32MB |
| 10. What order should I take your courses in (part 1).srt |
16.03KB |
| 11. Dynamic Programming Summary.mp4 |
8.31MB |
| 11. Dynamic Programming Summary.srt |
9.39KB |
| 11. Nonstationary Bandits.mp4 |
7.48MB |
| 11. Nonstationary Bandits.srt |
7.79KB |
| 11. Tic Tac Toe Summary.mp4 |
8.32MB |
| 11. Tic Tac Toe Summary.srt |
10.23KB |
| 11. What order should I take your courses in (part 2).mp4 |
37.62MB |
| 11. What order should I take your courses in (part 2).srt |
23.04KB |
| 12. Bandit Summary, Real Data, and Online Learning.mp4 |
33.92MB |
| 12. Bandit Summary, Real Data, and Online Learning.srt |
9.12KB |
| 12. BONUS Where to get discount coupons and FREE deep learning material.mp4 |
37.83MB |
| 12. BONUS Where to get discount coupons and FREE deep learning material.srt |
7.87KB |
| 12. Tic Tac Toe Exercise.mp4 |
19.77MB |
| 12. Tic Tac Toe Exercise.srt |
4.63KB |
| 2. Applications of the Explore-Exploit Dilemma.mp4 |
51.18MB |
| 2. Applications of the Explore-Exploit Dilemma.srt |
10.92KB |
| 2. Components of a Reinforcement Learning System.mp4 |
12.71MB |
| 2. Components of a Reinforcement Learning System.srt |
14.79KB |
| 2. Data and Environment.mp4 |
52.01MB |
| 2. Data and Environment.srt |
15.69KB |
| 2. Gridworld in Code.mp4 |
11.46MB |
| 2. Gridworld in Code.srt |
10.98KB |
| 2. Linear Models for Reinforcement Learning.mp4 |
6.47MB |
| 2. Linear Models for Reinforcement Learning.srt |
7.39KB |
| 2. Monte Carlo Policy Evaluation.mp4 |
8.75MB |
| 2. Monte Carlo Policy Evaluation.srt |
10.84KB |
| 2. On Unusual or Unexpected Strategies of RL.mp4 |
37.10MB |
| 2. On Unusual or Unexpected Strategies of RL.srt |
7.95KB |
| 2. TD(0) Prediction.mp4 |
5.82MB |
| 2. TD(0) Prediction.srt |
6.38KB |
| 2. The Markov Property.mp4 |
7.18MB |
| 2. The Markov Property.srt |
8.43KB |
| 2. Where to get the Code.mp4 |
4.45MB |
| 2. Where to get the Code.srt |
5.41KB |
| 2. Windows-Focused Environment Setup 2018.mp4 |
186.38MB |
| 2. Windows-Focused Environment Setup 2018.srt |
20.10KB |
| 3. Defining and Formalizing the MDP.mp4 |
6.64MB |
| 3. Defining and Formalizing the MDP.srt |
7.87KB |
| 3. Defining Some Terms.mp4 |
42.34MB |
| 3. Defining Some Terms.srt |
9.15KB |
| 3. Designing Your RL Program.mp4 |
22.34MB |
| 3. Designing Your RL Program.srt |
6.64KB |
| 3. Epsilon-Greedy.mp4 |
2.78MB |
| 3. Epsilon-Greedy.srt |
3.21KB |
| 3. Features.mp4 |
6.25MB |
| 3. Features.srt |
6.94KB |
| 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 |
43.92MB |
| 3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt |
18.33KB |
| 3. How to Model Q for Q-Learning.mp4 |
44.89MB |
| 3. How to Model Q for Q-Learning.srt |
12.01KB |
| 3. Monte Carlo Policy Evaluation in Code.mp4 |
7.92MB |
| 3. Monte Carlo Policy Evaluation in Code.srt |
6.12KB |
| 3. Notes on Assigning Rewards.mp4 |
4.22MB |
| 3. Notes on Assigning Rewards.srt |
4.94KB |
| 3. Strategy for Passing the Course.mp4 |
9.48MB |
| 3. Strategy for Passing the Course.srt |
11.77KB |
| 3. TD(0) Prediction in Code.mp4 |
5.32MB |
| 3. TD(0) Prediction in Code.srt |
3.97KB |
| 4. Course Outline.mp4 |
30.97MB |
| 4. Course Outline.srt |
6.81KB |
| 4. Design of the Program.mp4 |
23.31MB |
| 4. Design of the Program.srt |
8.51KB |
| 4. Future Rewards.mp4 |
5.17MB |
| 4. Future Rewards.srt |
6.01KB |
| 4. How to Code by Yourself (part 1).mp4 |
24.54MB |
| 4. How to Code by Yourself (part 1).srt |
30.21KB |
| 4. Iterative Policy Evaluation in Code.mp4 |
12.06MB |
| 4. Iterative Policy Evaluation in Code.srt |
10.24KB |
| 4. Monte Carlo Prediction with Approximation.mp4 |
2.85MB |
| 4. Monte Carlo Prediction with Approximation.srt |
2.34KB |
| 4. Policy Evaluation in Windy Gridworld.mp4 |
7.81MB |
| 4. Policy Evaluation in Windy Gridworld.srt |
5.30KB |
| 4. SARSA.mp4 |
8.20MB |
| 4. SARSA.srt |
9.70KB |
| 4. The Value Function and Your First Reinforcement Learning Algorithm.mp4 |
103.72MB |
| 4. The Value Function and Your First Reinforcement Learning Algorithm.srt |
22.78KB |
| 4. Updating a Sample Mean.mp4 |
2.18MB |
| 4. Updating a Sample Mean.srt |
2.17KB |
| 5. Code pt 1.mp4 |
49.72MB |
| 5. Code pt 1.srt |
9.63KB |
| 5. Designing Your Bandit Program.mp4 |
24.51MB |
| 5. Designing Your Bandit Program.srt |
5.61KB |
| 5. How to Code by Yourself (part 2).mp4 |
14.80MB |
| 5. How to Code by Yourself (part 2).srt |
18.42KB |
| 5. Monte Carlo Control.mp4 |
9.26MB |
| 5. Monte Carlo Control.srt |
10.24KB |
| 5. Monte Carlo Prediction with Approximation in Code.mp4 |
6.57MB |
| 5. Monte Carlo Prediction with Approximation in Code.srt |
4.01KB |
| 5. Policy Improvement.mp4 |
4.53MB |
| 5. Policy Improvement.srt |
5.17KB |
| 5. SARSA in Code.mp4 |
8.82MB |
| 5. SARSA in Code.srt |
5.53KB |
| 5. Tic Tac Toe Code Outline.mp4 |
5.04MB |
| 5. Tic Tac Toe Code Outline.srt |
6.42KB |
| 5. Value Function Introduction.mp4 |
19.72MB |
| 5. Value Function Introduction.srt |
15.63KB |
| 6. Code pt 2.mp4 |
65.29MB |
| 6. Code pt 2.srt |
11.75KB |
| 6. Comparing Different Epsilons.mp4 |
8.01MB |
| 6. Comparing Different Epsilons.srt |
5.32KB |
| 6. How to Succeed in this Course (Long Version).mp4 |
18.31MB |
| 6. How to Succeed in this Course (Long Version).srt |
14.55KB |
| 6. Monte Carlo Control in Code.mp4 |
10.17MB |
| 6. Monte Carlo Control in Code.srt |
5.83KB |
| 6. Policy Iteration.mp4 |
3.14MB |
| 6. Policy Iteration.srt |
3.47KB |
| 6. Q Learning.mp4 |
4.84MB |
| 6. Q Learning.srt |
5.82KB |
| 6. TD(0) Semi-Gradient Prediction.mp4 |
8.36MB |
| 6. TD(0) Semi-Gradient Prediction.srt |
6.36KB |
| 6. Tic Tac Toe Code Representing States.mp4 |
4.42MB |
| 6. Tic Tac Toe Code Representing States.srt |
4.92KB |
| 6. Value Functions.mp4 |
8.29MB |
| 6. Value Functions.srt |
11.76KB |
| 7. Bellman Examples.mp4 |
87.12MB |
| 7. Bellman Examples.srt |
27.67KB |
| 7. Code pt 3.mp4 |
33.72MB |
| 7. Code pt 3.srt |
5.41KB |
| 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 |
38.95MB |
| 7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt |
31.79KB |
| 7. Monte Carlo Control without Exploring Starts.mp4 |
4.62MB |
| 7. Monte Carlo Control without Exploring Starts.srt |
5.53KB |
| 7. Optimistic Initial Values.mp4 |
15.84MB |
| 7. Optimistic Initial Values.srt |
3.06KB |
| 7. Policy Iteration in Code.mp4 |
7.62MB |
| 7. Policy Iteration in Code.srt |
6.08KB |
| 7. Q Learning in Code.mp4 |
5.42MB |
| 7. Q Learning in Code.srt |
3.46KB |
| 7. Semi-Gradient SARSA.mp4 |
4.70MB |
| 7. Semi-Gradient SARSA.srt |
5.47KB |
| 7. Tic Tac Toe Code Enumerating States Recursively.mp4 |
9.79MB |
| 7. Tic Tac Toe Code Enumerating States Recursively.srt |
11.33KB |
| 8. Code pt 4.mp4 |
49.08MB |
| 8. Code pt 4.srt |
8.04KB |
| 8. Monte Carlo Control without Exploring Starts in Code.mp4 |
8.06MB |
| 8. Monte Carlo Control without Exploring Starts in Code.srt |
3.63KB |
| 8. Optimal Policy and Optimal Value Function.mp4 |
3.23MB |
| 8. Optimal Policy and Optimal Value Function.srt |
4.96KB |
| 8. Policy Iteration in Windy Gridworld.mp4 |
9.10MB |
| 8. Policy Iteration in Windy Gridworld.srt |
8.23KB |
| 8. Proof that using Jupyter Notebook is the same as not using it.mp4 |
78.32MB |
| 8. Proof that using Jupyter Notebook is the same as not using it.srt |
14.12KB |
| 8. Semi-Gradient SARSA in Code.mp4 |
10.61MB |
| 8. Semi-Gradient SARSA in Code.srt |
5.40KB |
| 8. TD Summary.mp4 |
3.94MB |
| 8. TD Summary.srt |
4.66KB |
| 8. Tic Tac Toe Code The Environment.mp4 |
10.05MB |
| 8. Tic Tac Toe Code The Environment.srt |
11.97KB |
| 8. UCB1.mp4 |
8.23MB |
| 8. UCB1.srt |
8.13KB |
| 9. Bayesian Thompson Sampling.mp4 |
51.85MB |
| 9. Bayesian Thompson Sampling.srt |
11.80KB |
| 9. Course Summary and Next Steps.mp4 |
13.24MB |
| 9. Course Summary and Next Steps.srt |
15.95KB |
| 9. MDP Summary.mp4 |
5.67MB |
| 9. MDP Summary.srt |
1.99KB |
| 9. Monte Carlo Summary.mp4 |
5.71MB |
| 9. Monte Carlo Summary.srt |
7.10KB |
| 9. Python 2 vs Python 3.mp4 |
7.84MB |
| 9. Python 2 vs Python 3.srt |
6.10KB |
| 9. Stock Trading Project Discussion.mp4 |
15.78MB |
| 9. Stock Trading Project Discussion.srt |
4.35KB |
| 9. Tic Tac Toe Code The Agent.mp4 |
9.01MB |
| 9. Tic Tac Toe Code The Agent.srt |
10.95KB |
| 9. Value Iteration.mp4 |
6.18MB |
| 9. Value Iteration.srt |
6.97KB |