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585B |
0 |
463.91KB |
1 |
229.21KB |
1. Approximation Methods Section Introduction.mp4 |
22.08MB |
1. Approximation Methods Section Introduction-en_US.srt |
5.60KB |
1. Beginners, halt! Stop here if you skipped ahead.mp4 |
83.78MB |
1. Beginners, halt! Stop here if you skipped ahead-en_US.srt |
19.90KB |
1. Dynamic Programming Section Introduction.mp4 |
34.67MB |
1. Dynamic Programming Section Introduction-en_US.srt |
11.91KB |
1. How to Code by Yourself (part 1).mp4 |
24.53MB |
1. How to Code by Yourself (part 1)-en_US.srt |
25.95KB |
1. How to Succeed in this Course (Long Version).mp4 |
18.31MB |
1. How to Succeed in this Course (Long Version)-en_US.srt |
14.00KB |
1. Introduction.mp4 |
34.24MB |
1. Introduction-en_US.srt |
4.03KB |
1. MDP Section Introduction.mp4 |
37.20MB |
1. MDP Section Introduction-en_US.srt |
8.02KB |
1. Monte Carlo Intro.mp4 |
47.59MB |
1. Monte Carlo Intro-en_US.srt |
12.12KB |
1. Section Introduction The Explore-Exploit Dilemma.mp4 |
51.99MB |
1. Section Introduction The Explore-Exploit Dilemma-en_US.srt |
12.99KB |
1. Temporal Difference Introduction.mp4 |
14.44MB |
1. Temporal Difference Introduction-en_US.srt |
5.04KB |
1. This Course vs. RL Book What's the Difference.mp4 |
38.21MB |
1. This Course vs. RL Book What's the Difference-en_US.srt |
9.89KB |
1. What is Reinforcement Learning.mp4 |
54.62MB |
1. What is Reinforcement Learning-en_US.srt |
10.51KB |
1. What is the Appendix.mp4 |
5.45MB |
1. What is the Appendix-en_US.srt |
3.58KB |
1. Windows-Focused Environment Setup 2018.mp4 |
186.38MB |
1. Windows-Focused Environment Setup 2018-en_US.srt |
19.29KB |
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280.95KB |
10. Approximation Methods Exercise.mp4 |
17.53MB |
10. Approximation Methods Exercise-en_US.srt |
5.13KB |
10. Optimistic Initial Values Beginner's Exercise Prompt.mp4 |
13.77MB |
10. Optimistic Initial Values Beginner's Exercise Prompt-en_US.srt |
2.82KB |
10. Policy Iteration in Code.mp4 |
56.38MB |
10. Policy Iteration in Code-en_US.srt |
10.39KB |
10. Stock Trading Project Discussion.mp4 |
15.78MB |
10. Stock Trading Project Discussion-en_US.srt |
4.19KB |
10. The Bellman Equation (pt 3).mp4 |
24.67MB |
10. The Bellman Equation (pt 3)-en_US.srt |
7.39KB |
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180.48KB |
11. Approximation Methods Section Summary.mp4 |
21.75MB |
11. Approximation Methods Section Summary-en_US.srt |
3.85KB |
11. Bellman Examples.mp4 |
87.12MB |
11. Bellman Examples-en_US.srt |
26.62KB |
11. Optimistic Initial Values Code.mp4 |
24.57MB |
11. Optimistic Initial Values Code-en_US.srt |
4.99KB |
11. Policy Iteration in Windy Gridworld.mp4 |
51.41MB |
11. Policy Iteration in Windy Gridworld-en_US.srt |
10.57KB |
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637.71KB |
12. Optimal Policy and Optimal Value Function (pt 1).mp4 |
56.06MB |
12. Optimal Policy and Optimal Value Function (pt 1)-en_US.srt |
11.04KB |
12. UCB1 Theory.mp4 |
55.53MB |
12. UCB1 Theory-en_US.srt |
19.19KB |
12. Value Iteration.mp4 |
35.27MB |
12. Value Iteration-en_US.srt |
9.31KB |
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13. Optimal Policy and Optimal Value Function (pt 2).mp4 |
15.72MB |
13. Optimal Policy and Optimal Value Function (pt 2)-en_US.srt |
4.91KB |
13. UCB1 Beginner's Exercise Prompt.mp4 |
12.74MB |
13. UCB1 Beginner's Exercise Prompt-en_US.srt |
2.65KB |
13. Value Iteration in Code.mp4 |
45.67MB |
13. Value Iteration in Code-en_US.srt |
8.51KB |
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97.75KB |
14. Dynamic Programming Summary.mp4 |
25.11MB |
14. Dynamic Programming Summary-en_US.srt |
6.28KB |
14. MDP Summary.mp4 |
14.28MB |
14. MDP Summary-en_US.srt |
3.46KB |
14. UCB1 Code.mp4 |
20.66MB |
14. UCB1 Code-en_US.srt |
3.59KB |
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485.31KB |
15. Bayesian Bandits Thompson Sampling Theory (pt 1).mp4 |
55.90MB |
15. Bayesian Bandits Thompson Sampling Theory (pt 1)-en_US.srt |
16.13KB |
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387.90KB |
16. Bayesian Bandits Thompson Sampling Theory (pt 2).mp4 |
74.50MB |
16. Bayesian Bandits Thompson Sampling Theory (pt 2)-en_US.srt |
22.71KB |
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10.86KB |
17. Thompson Sampling Beginner's Exercise Prompt.mp4 |
17.89MB |
17. Thompson Sampling Beginner's Exercise Prompt-en_US.srt |
3.26KB |
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64.50KB |
18. Thompson Sampling Code.mp4 |
32.83MB |
18. Thompson Sampling Code-en_US.srt |
5.43KB |
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1015.38KB |
19. Thompson Sampling With Gaussian Reward Theory.mp4 |
48.51MB |
19. Thompson Sampling With Gaussian Reward Theory-en_US.srt |
14.41KB |
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697.20KB |
2. Applications of the Explore-Exploit Dilemma.mp4 |
51.18MB |
2. Applications of the Explore-Exploit Dilemma-en_US.srt |
10.50KB |
2. BONUS Where to get discount coupons and FREE deep learning material.mp4 |
37.83MB |
2. BONUS Where to get discount coupons and FREE deep learning material-en_US.srt |
7.57KB |
2. Course Outline and Big Picture.mp4 |
39.68MB |
2. Course Outline and Big Picture-en_US.srt |
10.04KB |
2. From Bandits to Full Reinforcement Learning.mp4 |
41.19MB |
2. From Bandits to Full Reinforcement Learning-en_US.srt |
11.59KB |
2. Gridworld.mp4 |
53.99MB |
2. Gridworld-en_US.srt |
16.65KB |
2. How to Code by Yourself (part 2).mp4 |
14.80MB |
2. How to Code by Yourself (part 2)-en_US.srt |
15.79KB |
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 |
43.92MB |
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow-en_US.srt |
15.71KB |
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 |
38.95MB |
2. Iterative Policy Evaluation.mp4 |
60.82MB |
2. Iterative Policy Evaluation-en_US.srt |
20.37KB |
2. Linear Models for Reinforcement Learning.mp4 |
31.08MB |
2. Linear Models for Reinforcement Learning-en_US.srt |
10.97KB |
2. Monte Carlo Policy Evaluation.mp4 |
47.15MB |
2. Monte Carlo Policy Evaluation-en_US.srt |
14.07KB |
2. Stock Trading Project Section Introduction.mp4 |
26.76MB |
2. Stock Trading Project Section Introduction-en_US.srt |
6.58KB |
2. TD(0) Prediction.mp4 |
15.79MB |
2. TD(0) Prediction-en_US.srt |
6.64KB |
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5.42KB |
20. Thompson Sampling With Gaussian Reward Code.mp4 |
43.43MB |
20. Thompson Sampling With Gaussian Reward Code-en_US.srt |
6.97KB |
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361.41KB |
21. Why don't we just use a library.mp4 |
27.40MB |
21. Why don't we just use a library-en_US.srt |
7.32KB |
22 |
606.45KB |
22. Nonstationary Bandits.mp4 |
30.98MB |
22. Nonstationary Bandits-en_US.srt |
9.21KB |
23 |
840.72KB |
23. Bandit Summary, Real Data, and Online Learning.mp4 |
34.61MB |
23. Bandit Summary, Real Data, and Online Learning-en_US.srt |
8.76KB |
24 |
677.26KB |
24. (Optional) Alternative Bandit Designs.mp4 |
50.34MB |
24. (Optional) Alternative Bandit Designs-en_US.srt |
13.93KB |
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282.56KB |
25. Suggestion Box.mp4 |
16.13MB |
25. Suggestion Box-en_US.srt |
4.50KB |
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505.47KB |
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419.86KB |
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871.86KB |
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316.54KB |
3. Choosing Rewards.mp4 |
32.49MB |
3. Choosing Rewards-en_US.srt |
5.23KB |
3. Data and Environment.mp4 |
52.01MB |
3. Data and Environment-en_US.srt |
15.11KB |
3. Designing Your RL Program.mp4 |
22.34MB |
3. Designing Your RL Program-en_US.srt |
6.39KB |
3. Epsilon-Greedy Theory.mp4 |
28.30MB |
3. Epsilon-Greedy Theory-en_US.srt |
9.05KB |
3. External URLs.txt |
75B |
3. Feature Engineering.mp4 |
45.88MB |
3. Feature Engineering-en_US.srt |
13.90KB |
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 |
29.32MB |
3. Machine Learning and AI Prerequisite Roadmap (pt 1)-en_US.srt |
15.45KB |
3. Monte Carlo Policy Evaluation in Code.mp4 |
51.65MB |
3. Monte Carlo Policy Evaluation in Code-en_US.srt |
10.17KB |
3. Proof that using Jupyter Notebook is the same as not using it.mp4 |
78.32MB |
3. Proof that using Jupyter Notebook is the same as not using it-en_US.srt |
13.54KB |
3. TD(0) Prediction in Code.mp4 |
32.43MB |
3. TD(0) Prediction in Code-en_US.srt |
5.80KB |
3. Where to get the Code.mp4 |
22.72MB |
3. Where to get the Code-en_US.srt |
6.05KB |
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127.63KB |
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181.04KB |
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355.22KB |
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511.05KB |
4. Approximation Methods for Prediction.mp4 |
34.34MB |
4. Approximation Methods for Prediction-en_US.srt |
12.06KB |
4. Calculating a Sample Mean (pt 1).mp4 |
23.13MB |
4. Calculating a Sample Mean (pt 1)-en_US.srt |
7.22KB |
4. Gridworld in Code.mp4 |
46.79MB |
4. Gridworld in Code-en_US.srt |
15.72KB |
4. How to Model Q for Q-Learning.mp4 |
44.89MB |
4. How to Model Q for Q-Learning-en_US.srt |
11.58KB |
4. How to Succeed in this Course.mp4 |
43.82MB |
4. How to Succeed in this Course-en_US.srt |
7.94KB |
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 |
37.62MB |
4. Machine Learning and AI Prerequisite Roadmap (pt 2)-en_US.srt |
22.21KB |
4. Monte Carlo Control.mp4 |
35.61MB |
4. Monte Carlo Control-en_US.srt |
11.16KB |
4. Python 2 vs Python 3.mp4 |
7.83MB |
4. Python 2 vs Python 3-en_US.srt |
5.86KB |
4. SARSA.mp4 |
16.22MB |
4. SARSA-en_US.srt |
5.77KB |
4. The Markov Property.mp4 |
21.76MB |
4. The Markov Property-en_US.srt |
7.70KB |
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583.75KB |
5. Approximation Methods for Prediction Code.mp4 |
62.29MB |
5. Approximation Methods for Prediction Code-en_US.srt |
10.20KB |
5. Design of the Program.mp4 |
23.31MB |
5. Design of the Program-en_US.srt |
8.19KB |
5. Epsilon-Greedy Beginner's Exercise Prompt.mp4 |
28.66MB |
5. Epsilon-Greedy Beginner's Exercise Prompt-en_US.srt |
6.15KB |
5. Iterative Policy Evaluation in Code.mp4 |
68.43MB |
5. Iterative Policy Evaluation in Code-en_US.srt |
15.64KB |
5. Markov Decision Processes (MDPs).mp4 |
61.73MB |
5. Markov Decision Processes (MDPs)-en_US.srt |
18.85KB |
5. Monte Carlo Control in Code.mp4 |
64.41MB |
5. Monte Carlo Control in Code-en_US.srt |
10.74KB |
5. SARSA in Code.mp4 |
44.90MB |
5. SARSA in Code-en_US.srt |
7.40KB |
5. Warmup.mp4 |
62.60MB |
5. Warmup-en_US.srt |
18.14KB |
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6. Approximation Methods for Control.mp4 |
17.59MB |
6. Approximation Methods for Control-en_US.srt |
5.49KB |
6. Code pt 1.mp4 |
49.72MB |
6. Code pt 1-en_US.srt |
9.28KB |
6. Designing Your Bandit Program.mp4 |
24.51MB |
6. Designing Your Bandit Program-en_US.srt |
5.41KB |
6. Future Rewards.mp4 |
39.50MB |
6. Future Rewards-en_US.srt |
12.19KB |
6. Monte Carlo Control without Exploring Starts.mp4 |
23.40MB |
6. Monte Carlo Control without Exploring Starts-en_US.srt |
5.60KB |
6. Q Learning.mp4 |
19.82MB |
6. Q Learning-en_US.srt |
6.09KB |
6. Windy Gridworld in Code.mp4 |
41.45MB |
6. Windy Gridworld in Code-en_US.srt |
10.04KB |
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7. Approximation Methods for Control Code.mp4 |
77.69MB |
7. Approximation Methods for Control Code-en_US.srt |
10.55KB |
7. Code pt 2.mp4 |
65.29MB |
7. Code pt 2-en_US.srt |
11.31KB |
7. Epsilon-Greedy in Code.mp4 |
41.43MB |
7. Epsilon-Greedy in Code-en_US.srt |
8.30KB |
7. Iterative Policy Evaluation for Windy Gridworld in Code.mp4 |
46.93MB |
7. Iterative Policy Evaluation for Windy Gridworld in Code-en_US.srt |
9.34KB |
7. Monte Carlo Control without Exploring Starts in Code.mp4 |
40.69MB |
7. Monte Carlo Control without Exploring Starts in Code-en_US.srt |
6.91KB |
7. Q Learning in Code.mp4 |
38.55MB |
7. Q Learning in Code-en_US.srt |
5.83KB |
7. Value Functions.mp4 |
18.55MB |
7. Value Functions-en_US.srt |
6.38KB |
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8. CartPole.mp4 |
26.90MB |
8. CartPole-en_US.srt |
6.99KB |
8. Code pt 3.mp4 |
33.72MB |
8. Code pt 3-en_US.srt |
5.20KB |
8. Comparing Different Epsilons.mp4 |
43.65MB |
8. Comparing Different Epsilons-en_US.srt |
6.51KB |
8. Monte Carlo Summary.mp4 |
11.40MB |
8. Monte Carlo Summary-en_US.srt |
2.08KB |
8. Policy Improvement.mp4 |
43.99MB |
8. Policy Improvement-en_US.srt |
14.18KB |
8. TD Learning Section Summary.mp4 |
10.04MB |
8. TD Learning Section Summary-en_US.srt |
2.85KB |
8. The Bellman Equation (pt 1).mp4 |
27.78MB |
8. The Bellman Equation (pt 1)-en_US.srt |
10.68KB |
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705.04KB |
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9. CartPole Code.mp4 |
46.83MB |
9. CartPole Code-en_US.srt |
6.52KB |
9. Code pt 4.mp4 |
52.94MB |
9. Code pt 4-en_US.srt |
7.94KB |
9. Optimistic Initial Values Theory.mp4 |
23.52MB |
9. Optimistic Initial Values Theory-en_US.srt |
6.87KB |
9. Policy Iteration.mp4 |
34.15MB |
9. Policy Iteration-en_US.srt |
9.99KB |
9. The Bellman Equation (pt 2).mp4 |
26.69MB |
9. The Bellman Equation (pt 2)-en_US.srt |
8.24KB |
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TutsNode.com.txt |
63B |