| 1. Approximation Methods Section Introduction-en_US.srt | 5.6 KB | ||
| 1. Approximation Methods Section Introduction.mp4 | 22.1 MB | ||
| 1. Beginners, halt! Stop here if you skipped ahead-en_US.srt | 19.9 KB | ||
| 1. Beginners, halt! Stop here if you skipped ahead.mp4 | 83.8 MB | ||
| 1. Dynamic Programming Section Introduction-en_US.srt | 11.9 KB | ||
| 1. Dynamic Programming Section Introduction.mp4 | 34.7 MB | ||
| 1. How to Code by Yourself (part 1)-en_US.srt | 26 KB | ||
| 1. How to Code by Yourself (part 1).mp4 | 24.5 MB | ||
| 1. How to Succeed in this Course (Long Version)-en_US.srt | 14 KB | ||
| 1. How to Succeed in this Course (Long Version).mp4 | 18.3 MB | ||
| 1. Introduction-en_US.srt | 4 KB | ||
| 1. Introduction.mp4 | 34.2 MB | ||
| 1. MDP Section Introduction-en_US.srt | 8 KB | ||
| 1. MDP Section Introduction.mp4 | 37.2 MB | ||
| 1. Monte Carlo Intro-en_US.srt | 12.1 KB | ||
| 1. Monte Carlo Intro.mp4 | 47.6 MB | ||
| 1. Section Introduction The Explore-Exploit Dilemma-en_US.srt | 13 KB | ||
| 1. Section Introduction The Explore-Exploit Dilemma.mp4 | 52 MB | ||
| 1. Temporal Difference Introduction-en_US.srt | 5 KB | ||
| 1. Temporal Difference Introduction.mp4 | 14.4 MB | ||
| 1. This Course vs. RL Book What's the Difference-en_US.srt | 9.9 KB | ||
| 1. This Course vs. RL Book What's the Difference.mp4 | 38.2 MB | ||
| 1. What is Reinforcement Learning-en_US.srt | 10.5 KB | ||
| 1. What is Reinforcement Learning.mp4 | 54.6 MB | ||
| 1. What is the Appendix-en_US.srt | 3.6 KB | ||
| 1. What is the Appendix.mp4 | 5.5 MB | ||
| 1. Windows-Focused Environment Setup 2018-en_US.srt | 19.3 KB | ||
| 1. Windows-Focused Environment Setup 2018.mp4 | 186.4 MB | ||
| 10. Approximation Methods Exercise-en_US.srt | 5.1 KB | ||
| 10. Approximation Methods Exercise.mp4 | 17.5 MB | ||
| 10. Optimistic Initial Values Beginner's Exercise Prompt-en_US.srt | 2.8 KB | ||
| 10. Optimistic Initial Values Beginner's Exercise Prompt.mp4 | 13.8 MB | ||
| 10. Policy Iteration in Code-en_US.srt | 10.4 KB | ||
| 10. Policy Iteration in Code.mp4 | 56.4 MB | ||
| 10. Stock Trading Project Discussion-en_US.srt | 4.2 KB | ||
| 10. Stock Trading Project Discussion.mp4 | 15.8 MB | ||
| 10. The Bellman Equation (pt 3)-en_US.srt | 7.4 KB | ||
| 10. The Bellman Equation (pt 3).mp4 | 24.7 MB | ||
| 11. Approximation Methods Section Summary-en_US.srt | 3.8 KB | ||
| 11. Approximation Methods Section Summary.mp4 | 21.8 MB | ||
| 11. Bellman Examples-en_US.srt | 26.6 KB | ||
| 11. Bellman Examples.mp4 | 87.1 MB | ||
| 11. Optimistic Initial Values Code-en_US.srt | 5 KB | ||
| 11. Optimistic Initial Values Code.mp4 | 24.6 MB | ||
| 11. Policy Iteration in Windy Gridworld-en_US.srt | 10.6 KB | ||
| 11. Policy Iteration in Windy Gridworld.mp4 | 51.4 MB | ||
| 12. Optimal Policy and Optimal Value Function (pt 1)-en_US.srt | 11 KB | ||
| 12. Optimal Policy and Optimal Value Function (pt 1).mp4 | 56.1 MB | ||
| 12. UCB1 Theory-en_US.srt | 19.2 KB | ||
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| 12. Value Iteration-en_US.srt | 9.3 KB | ||
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| 13. Optimal Policy and Optimal Value Function (pt 2)-en_US.srt | 4.9 KB | ||
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| 13. UCB1 Beginner's Exercise Prompt-en_US.srt | 2.6 KB | ||
| 13. UCB1 Beginner's Exercise Prompt.mp4 | 12.7 MB | ||
| 13. Value Iteration in Code-en_US.srt | 8.5 KB | ||
| 13. Value Iteration in Code.mp4 | 45.7 MB | ||
| 14. Dynamic Programming Summary-en_US.srt | 6.3 KB | ||
| 14. Dynamic Programming Summary.mp4 | 25.1 MB | ||
| 14. MDP Summary-en_US.srt | 3.5 KB | ||
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| 14. UCB1 Code-en_US.srt | 3.6 KB | ||
| 14. UCB1 Code.mp4 | 20.7 MB | ||
| 15. Bayesian Bandits Thompson Sampling Theory (pt 1)-en_US.srt | 16.1 KB | ||
| 15. Bayesian Bandits Thompson Sampling Theory (pt 1).mp4 | 55.9 MB | ||
| 16. Bayesian Bandits Thompson Sampling Theory (pt 2)-en_US.srt | 22.7 KB | ||
| 16. Bayesian Bandits Thompson Sampling Theory (pt 2).mp4 | 74.5 MB | ||
| 17. Thompson Sampling Beginner's Exercise Prompt-en_US.srt | 3.3 KB | ||
| 17. Thompson Sampling Beginner's Exercise Prompt.mp4 | 17.9 MB | ||
| 18. Thompson Sampling Code-en_US.srt | 5.4 KB | ||
| 18. Thompson Sampling Code.mp4 | 32.8 MB | ||
| 19. Thompson Sampling With Gaussian Reward Theory-en_US.srt | 14.4 KB | ||
| 19. Thompson Sampling With Gaussian Reward Theory.mp4 | 48.5 MB | ||
| 2. Applications of the Explore-Exploit Dilemma-en_US.srt | 10.5 KB | ||
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| 2. BONUS Where to get discount coupons and FREE deep learning material-en_US.srt | 7.6 KB | ||
| 2. BONUS Where to get discount coupons and FREE deep learning material.mp4 | 37.8 MB | ||
| 2. Course Outline and Big Picture-en_US.srt | 10 KB | ||
| 2. Course Outline and Big Picture.mp4 | 39.7 MB | ||
| 2. From Bandits to Full Reinforcement Learning-en_US.srt | 11.6 KB | ||
| 2. From Bandits to Full Reinforcement Learning.mp4 | 41.2 MB | ||
| 2. Gridworld-en_US.srt | 16.6 KB | ||
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| 2. How to Code by Yourself (part 2)-en_US.srt | 15.8 KB | ||
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| 2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow-en_US.srt | 15.7 KB | ||
| 2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 | 43.9 MB | ||
| 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 | 39 MB | ||
| 2. Iterative Policy Evaluation-en_US.srt | 20.4 KB | ||
| 2. Iterative Policy Evaluation.mp4 | 60.8 MB | ||
| 2. Linear Models for Reinforcement Learning-en_US.srt | 11 KB | ||
| 2. Linear Models for Reinforcement Learning.mp4 | 31.1 MB | ||
| 2. Monte Carlo Policy Evaluation-en_US.srt | 14.1 KB | ||
| 2. Monte Carlo Policy Evaluation.mp4 | 47.1 MB | ||
| 2. Stock Trading Project Section Introduction-en_US.srt | 6.6 KB | ||
| 2. Stock Trading Project Section Introduction.mp4 | 26.8 MB | ||
| 2. TD(0) Prediction-en_US.srt | 6.6 KB | ||
| 2. TD(0) Prediction.mp4 | 15.8 MB | ||
| 20. Thompson Sampling With Gaussian Reward Code-en_US.srt | 7 KB | ||
| 20. Thompson Sampling With Gaussian Reward Code.mp4 | 43.4 MB | ||
| 21. Why don't we just use a library-en_US.srt | 7.3 KB | ||
| 21. Why don't we just use a library.mp4 | 27.4 MB | ||
| 22. Nonstationary Bandits-en_US.srt | 9.2 KB | ||
| 22. Nonstationary Bandits.mp4 | 31 MB | ||
| 23. Bandit Summary, Real Data, and Online Learning-en_US.srt | 8.8 KB | ||
| 23. Bandit Summary, Real Data, and Online Learning.mp4 | 34.6 MB | ||
| 24. (Optional) Alternative Bandit Designs-en_US.srt | 13.9 KB | ||
| 24. (Optional) Alternative Bandit Designs.mp4 | 50.3 MB | ||
| 25. Suggestion Box-en_US.srt | 4.5 KB | ||
| 25. Suggestion Box.mp4 | 16.1 MB | ||
| 3. Choosing Rewards-en_US.srt | 5.2 KB | ||
| 3. Choosing Rewards.mp4 | 32.5 MB | ||
| 3. Data and Environment-en_US.srt | 15.1 KB | ||
| 3. Data and Environment.mp4 | 52 MB | ||
| 3. Designing Your RL Program-en_US.srt | 6.4 KB | ||
| 3. Designing Your RL Program.mp4 | 22.3 MB | ||
| 3. Epsilon-Greedy Theory-en_US.srt | 9.1 KB | ||
| 3. Epsilon-Greedy Theory.mp4 | 28.3 MB | ||
| 3. External URLs.txt | 102.4 B | ||
| 3. Feature Engineering-en_US.srt | 13.9 KB | ||
| 3. Feature Engineering.mp4 | 45.9 MB | ||
| 3. Machine Learning and AI Prerequisite Roadmap (pt 1)-en_US.srt | 15.4 KB | ||
| 3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 | 29.3 MB | ||
| 3. Monte Carlo Policy Evaluation in Code-en_US.srt | 10.2 KB | ||
| 3. Monte Carlo Policy Evaluation in Code.mp4 | 51.6 MB | ||
| 3. Proof that using Jupyter Notebook is the same as not using it-en_US.srt | 13.5 KB | ||
| 3. Proof that using Jupyter Notebook is the same as not using it.mp4 | 78.3 MB | ||
| 3. TD(0) Prediction in Code-en_US.srt | 5.8 KB | ||
| 3. TD(0) Prediction in Code.mp4 | 32.4 MB | ||
| 3. Where to get the Code-en_US.srt | 6.1 KB | ||
| 3. Where to get the Code.mp4 | 22.7 MB | ||
| 4. Approximation Methods for Prediction-en_US.srt | 12.1 KB | ||
| 4. Approximation Methods for Prediction.mp4 | 34.3 MB | ||
| 4. Calculating a Sample Mean (pt 1)-en_US.srt | 7.2 KB | ||
| 4. Calculating a Sample Mean (pt 1).mp4 | 23.1 MB | ||
| 4. Gridworld in Code-en_US.srt | 15.7 KB | ||
| 4. Gridworld in Code.mp4 | 46.8 MB | ||
| 4. How to Model Q for Q-Learning-en_US.srt | 11.6 KB | ||
| 4. How to Model Q for Q-Learning.mp4 | 44.9 MB | ||
| 4. How to Succeed in this Course-en_US.srt | 7.9 KB | ||
| 4. How to Succeed in this Course.mp4 | 43.8 MB | ||
| 4. Machine Learning and AI Prerequisite Roadmap (pt 2)-en_US.srt | 22.2 KB | ||
| 4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 | 37.6 MB | ||
| 4. Monte Carlo Control-en_US.srt | 11.2 KB | ||
| 4. Monte Carlo Control.mp4 | 35.6 MB | ||
| 4. Python 2 vs Python 3-en_US.srt | 5.9 KB | ||
| 4. Python 2 vs Python 3.mp4 | 7.8 MB | ||
| 4. SARSA-en_US.srt | 5.8 KB | ||
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| 4. The Markov Property-en_US.srt | 7.7 KB | ||
| 4. The Markov Property.mp4 | 21.8 MB | ||
| 5. Approximation Methods for Prediction Code-en_US.srt | 10.2 KB | ||
| 5. Approximation Methods for Prediction Code.mp4 | 62.3 MB | ||
| 5. Design of the Program-en_US.srt | 8.2 KB | ||
| 5. Design of the Program.mp4 | 23.3 MB | ||
| 5. Epsilon-Greedy Beginner's Exercise Prompt-en_US.srt | 6.2 KB | ||
| 5. Epsilon-Greedy Beginner's Exercise Prompt.mp4 | 28.7 MB | ||
| 5. Iterative Policy Evaluation in Code-en_US.srt | 15.6 KB | ||
| 5. Iterative Policy Evaluation in Code.mp4 | 68.4 MB | ||
| 5. Markov Decision Processes (MDPs)-en_US.srt | 18.8 KB | ||
| 5. Markov Decision Processes (MDPs).mp4 | 61.7 MB | ||
| 5. Monte Carlo Control in Code-en_US.srt | 10.7 KB | ||
| 5. Monte Carlo Control in Code.mp4 | 64.4 MB | ||
| 5. SARSA in Code-en_US.srt | 7.4 KB | ||
| 5. SARSA in Code.mp4 | 44.9 MB | ||
| 5. Warmup-en_US.srt | 18.1 KB | ||
| 5. Warmup.mp4 | 62.6 MB | ||
| 6. Approximation Methods for Control-en_US.srt | 5.5 KB | ||
| 6. Approximation Methods for Control.mp4 | 17.6 MB | ||
| 6. Code pt 1-en_US.srt | 9.3 KB | ||
| 6. Code pt 1.mp4 | 49.7 MB | ||
| 6. Designing Your Bandit Program-en_US.srt | 5.4 KB | ||
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| 6. Future Rewards-en_US.srt | 12.2 KB | ||
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| 6. Monte Carlo Control without Exploring Starts-en_US.srt | 5.6 KB | ||
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| 6. Q Learning-en_US.srt | 6.1 KB | ||
| 6. Q Learning.mp4 | 19.8 MB | ||
| 6. Windy Gridworld in Code-en_US.srt | 10 KB | ||
| 6. Windy Gridworld in Code.mp4 | 41.5 MB | ||
| 7. Approximation Methods for Control Code-en_US.srt | 10.5 KB | ||
| 7. Approximation Methods for Control Code.mp4 | 77.7 MB | ||
| 7. Code pt 2-en_US.srt | 11.3 KB | ||
| 7. Code pt 2.mp4 | 65.3 MB | ||
| 7. Epsilon-Greedy in Code-en_US.srt | 8.3 KB | ||
| 7. Epsilon-Greedy in Code.mp4 | 41.4 MB | ||
| 7. Iterative Policy Evaluation for Windy Gridworld in Code-en_US.srt | 9.3 KB | ||
| 7. Iterative Policy Evaluation for Windy Gridworld in Code.mp4 | 46.9 MB | ||
| 7. Monte Carlo Control without Exploring Starts in Code-en_US.srt | 6.9 KB | ||
| 7. Monte Carlo Control without Exploring Starts in Code.mp4 | 40.7 MB | ||
| 7. Q Learning in Code-en_US.srt | 5.8 KB | ||
| 7. Q Learning in Code.mp4 | 38.5 MB | ||
| 7. Value Functions-en_US.srt | 6.4 KB | ||
| 7. Value Functions.mp4 | 18.5 MB | ||
| 8. CartPole-en_US.srt | 7 KB | ||
| 8. CartPole.mp4 | 26.9 MB | ||
| 8. Code pt 3-en_US.srt | 5.2 KB | ||
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| 8. Comparing Different Epsilons-en_US.srt | 6.5 KB | ||
| 8. Comparing Different Epsilons.mp4 | 43.7 MB | ||
| 8. Monte Carlo Summary-en_US.srt | 2.1 KB | ||
| 8. Monte Carlo Summary.mp4 | 11.4 MB | ||
| 8. Policy Improvement-en_US.srt | 14.2 KB | ||
| 8. Policy Improvement.mp4 | 44 MB | ||
| 8. TD Learning Section Summary-en_US.srt | 2.9 KB | ||
| 8. TD Learning Section Summary.mp4 | 10 MB | ||
| 8. The Bellman Equation (pt 1)-en_US.srt | 10.7 KB | ||
| 8. The Bellman Equation (pt 1).mp4 | 27.8 MB | ||
| 9. CartPole Code-en_US.srt | 6.5 KB | ||
| 9. CartPole Code.mp4 | 46.8 MB | ||
| 9. Code pt 4-en_US.srt | 7.9 KB | ||
| 9. Code pt 4.mp4 | 52.9 MB | ||
| 9. Optimistic Initial Values Theory-en_US.srt | 6.9 KB | ||
| 9. Optimistic Initial Values Theory.mp4 | 23.5 MB | ||
| 9. Policy Iteration-en_US.srt | 10 KB | ||
| 9. Policy Iteration.mp4 | 34.2 MB | ||
| 9. The Bellman Equation (pt 2)-en_US.srt | 8.2 KB | ||
| 9. The Bellman Equation (pt 2).mp4 | 26.7 MB | ||
| [CourseClub.ME].url | 102.4 B | ||
| [CourseClub.Me].url | 102.4 B | ||
| [GigaCourse.Com].url | 0 B | ||
| ▲ 228 total files | |||
Udemy - Artificial Intelligence: Reinforcement Learning in Python [Giga Course]
Complete guide to artificial intelligence and machine learning, prep for deep reinforcement learning
Created by Lazy Programmer Inc.
Last updated 6/2021
English
English [Auto-generated]
For More Udemy Courses Visit: https://gigacourse.com
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.8 GB | freecoursewb | 4 weeks | 11 | 5 | |
| 1.8 GB | freecoursewb | 2 months | 13 | 11 | |
| 2 GB | freecoursewb | 2 months | 27 | 34 | |
| 1.9 GB | freecoursewb | 3 months | 5 | 3 | |
| 2 GB | freecoursewb | 4 months | 15 | 8 |
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