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[Tutorialsplanet.NET] Udemy - Artificial Intelligence Reinforcement Learning in Python
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3.12 GB
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Uploaded:
Mar 13, 2022
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[Tutorialsplanet.NET] Udemy - Artificial Intelligence Reinforcement Learning in Python
10
1. Windows-Focused Environment Setup 2018.mp4
- 186.39 MB
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
- 43.92 MB
1. Windows-Focused Environment Setup 2018.srt
- 20.1 KB
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt
- 18.33 KB
4. Markov Decision Proccesses
11. Bellman Examples.mp4
- 87.13 MB
5. Markov Decision Processes (MDPs).mp4
- 61.74 MB
12. Optimal Policy and Optimal Value Function (pt 1).mp4
- 56.07 MB
2. Gridworld.mp4
- 54 MB
6. Future Rewards.mp4
- 39.51 MB
1. MDP Section Introduction.mp4
- 37.2 MB
3. Choosing Rewards.mp4
- 32.5 MB
8. The Bellman Equation (pt 1).mp4
- 27.79 MB
9. The Bellman Equation (pt 2).mp4
- 26.7 MB
10. The Bellman Equation (pt 3).mp4
- 24.67 MB
4. The Markov Property.mp4
- 21.77 MB
7. Value Functions.srt
- 18.58 MB
7. Value Functions.mp4
- 18.55 MB
13. Optimal Policy and Optimal Value Function (pt 2).mp4
- 15.73 MB
14. MDP Summary.mp4
- 14.28 MB
11. Bellman Examples.srt
- 29.16 KB
5. Markov Decision Processes (MDPs).srt
- 21.85 KB
2. Gridworld.srt
- 19.11 KB
6. Future Rewards.srt
- 14.19 KB
12. Optimal Policy and Optimal Value Function (pt 1).srt
- 12.76 KB
8. The Bellman Equation (pt 1).srt
- 12.27 KB
9. The Bellman Equation (pt 2).srt
- 9.48 KB
1. MDP Section Introduction.srt
- 9.36 KB
4. The Markov Property.srt
- 8.87 KB
10. The Bellman Equation (pt 3).srt
- 8.66 KB
3. Choosing Rewards.srt
- 5.85 KB
13. Optimal Policy and Optimal Value Function (pt 2).srt
- 5.47 KB
14. MDP Summary.srt
- 3.99 KB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)
3. Proof that using Jupyter Notebook is the same as not using it.mp4
- 78.33 MB
1. How to Code by Yourself (part 1).mp4
- 24.54 MB
2. How to Code by Yourself (part 2).mp4
- 14.8 MB
4. Python 2 vs Python 3.mp4
- 7.84 MB
1. How to Code by Yourself (part 1).srt
- 30.21 KB
2. How to Code by Yourself (part 2).srt
- 18.42 KB
3. Proof that using Jupyter Notebook is the same as not using it.srt
- 14.12 KB
4. Python 2 vs Python 3.srt
- 6.1 KB
2. Return of the Multi-Armed Bandit
16. Bayesian Bandits Thompson Sampling Theory (pt 2).mp4
- 74.51 MB
15. Bayesian Bandits Thompson Sampling Theory (pt 1).mp4
- 55.9 MB
12. UCB1 Theory.mp4
- 55.54 MB
1. Section Introduction The Explore-Exploit Dilemma.mp4
- 52 MB
2. Applications of the Explore-Exploit Dilemma.mp4
- 51.19 MB
24. (Optional) Alternative Bandit Designs.mp4
- 50.34 MB
19. Thompson Sampling With Gaussian Reward Theory.mp4
- 48.52 MB
8. Comparing Different Epsilons.mp4
- 43.66 MB
20. Thompson Sampling With Gaussian Reward Code.mp4
- 43.43 MB
7. Epsilon-Greedy in Code.mp4
- 41.44 MB
23. Bandit Summary, Real Data, and Online Learning.mp4
- 34.62 MB
18. Thompson Sampling Code.mp4
- 32.83 MB
22. Nonstationary Bandits.mp4
- 30.99 MB
5. Epsilon-Greedy Beginner's Exercise Prompt.mp4
- 28.67 MB
3. Epsilon-Greedy Theory.mp4
- 28.31 MB
21. Why don't we just use a library.mp4
- 27.41 MB
11. Optimistic Initial Values Code.mp4
- 24.58 MB
6. Designing Your Bandit Program.mp4
- 24.51 MB
9. Optimistic Initial Values Theory.mp4
- 23.53 MB
4. Calculating a Sample Mean (pt 1).mp4
- 23.13 MB
14. UCB1 Code.mp4
- 20.66 MB
17. Thompson Sampling Beginner's Exercise Prompt.mp4
- 17.9 MB
25. Suggestion Box.mp4
- 16.13 MB
10. Optimistic Initial Values Beginner's Exercise Prompt.mp4
- 13.77 MB
13. UCB1 Beginner's Exercise Prompt.mp4
- 12.74 MB
16. Bayesian Bandits Thompson Sampling Theory (pt 2).srt
- 25.73 KB
12. UCB1 Theory.srt
- 21.98 KB
15. Bayesian Bandits Thompson Sampling Theory (pt 1).srt
- 18.35 KB
19. Thompson Sampling With Gaussian Reward Theory.srt
- 16.53 KB
24. (Optional) Alternative Bandit Designs.srt
- 15.1 KB
1. Section Introduction The Explore-Exploit Dilemma.srt
- 14.73 KB
2. Applications of the Explore-Exploit Dilemma.srt
- 11.7 KB
3. Epsilon-Greedy Theory.srt
- 10.43 KB
22. Nonstationary Bandits.srt
- 10.2 KB
23. Bandit Summary, Real Data, and Online Learning.srt
- 10.08 KB
7. Epsilon-Greedy in Code.srt
- 9.39 KB
4. Calculating a Sample Mean (pt 1).srt
- 8.49 KB
21. Why don't we just use a library.srt
- 8.38 KB
20. Thompson Sampling With Gaussian Reward Code.srt
- 8.09 KB
9. Optimistic Initial Values Theory.srt
- 7.92 KB
5. Epsilon-Greedy Beginner's Exercise Prompt.srt
- 7.11 KB
8. Comparing Different Epsilons.srt
- 7.03 KB
18. Thompson Sampling Code.srt
- 6.32 KB
6. Designing Your Bandit Program.srt
- 5.98 KB
11. Optimistic Initial Values Code.srt
- 5.78 KB
25. Suggestion Box.srt
- 5.05 KB
14. UCB1 Code.srt
- 4.26 KB
17. Thompson Sampling Beginner's Exercise Prompt.srt
- 3.8 KB
10. Optimistic Initial Values Beginner's Exercise Prompt.srt
- 3.11 KB
13. UCB1 Beginner's Exercise Prompt.srt
- 3.04 KB
5. Dynamic Programming
4. Iterative Policy Evaluation in Code.mp4
- 68.44 MB
9. Policy Iteration in Code.mp4
- 56.39 MB
10. Policy Iteration in Windy Gridworld.mp4
- 51.41 MB
6. Iterative Policy Evaluation for Windy Gridworld in Code.mp4
- 46.93 MB
3. Gridworld in Code.mp4
- 46.8 MB
12. Value Iteration in Code.mp4
- 45.67 MB
5. Windy Gridworld in Code.mp4
- 41.46 MB
2. Designing Your RL Program.mp4
- 22.35 MB
13. Dynamic Programming Summary.mp4
- 8.31 MB
11. Value Iteration.mp4
- 6.18 MB
1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4
- 4.84 MB
7. Policy Improvement.mp4
- 4.53 MB
8. Policy Iteration.mp4
- 3.13 MB
4. Iterative Policy Evaluation in Code.srt
- 18.03 KB
3. Gridworld in Code.srt
- 18.03 KB
10. Policy Iteration in Windy Gridworld.srt
- 12.27 KB
9. Policy Iteration in Code.srt
- 12.2 KB
5. Windy Gridworld in Code.srt
- 11.16 KB
6. Iterative Policy Evaluation for Windy Gridworld in Code.srt
- 10.89 KB
12. Value Iteration in Code.srt
- 9.83 KB
13. Dynamic Programming Summary.srt
- 9.39 KB
2. Designing Your RL Program.srt
- 7.05 KB
11. Value Iteration.srt
- 6.97 KB
1. Intro to Dynamic Programming and Iterative Policy Evaluation.srt
- 5.37 KB
7. Policy Improvement.srt
- 5.17 KB
8. Policy Iteration.srt
- 3.47 KB
9. Stock Trading Project with Reinforcement Learning
6. Code pt 2.mp4
- 65.29 MB
2. Data and Environment.mp4
- 52.01 MB
5. Code pt 1.mp4
- 49.73 MB
8. Code pt 4.mp4
- 49.09 MB
3. How to Model Q for Q-Learning.mp4
- 44.9 MB
7. Code pt 3.mp4
- 33.73 MB
1. Stock Trading Project Section Introduction.mp4
- 26.77 MB
4. Design of the Program.mp4
- 23.32 MB
9. Stock Trading Project Discussion.mp4
- 15.79 MB
2. Data and Environment.srt
- 16.59 KB
3. How to Model Q for Q-Learning.srt
- 12.95 KB
6. Code pt 2.srt
- 12.77 KB
5. Code pt 1.srt
- 10.4 KB
4. Design of the Program.srt
- 9.3 KB
8. Code pt 4.srt
- 8.79 KB
1. Stock Trading Project Section Introduction.srt
- 7.16 KB
7. Code pt 3.srt
- 5.85 KB
9. Stock Trading Project Discussion.srt
- 4.63 KB
1. Welcome
5. Warmup.mp4
- 62.61 MB
2. Course Outline and Big Picture.mp4
- 39.69 MB
1. Introduction.mp4
- 34.24 MB
3. Where to get the Code.mp4
- 22.73 MB
4. How to Succeed in this Course.mp4
- 15.72 MB
5. Warmup.srt
- 19.57 KB
2. Course Outline and Big Picture.srt
- 11.16 KB
3. Where to get the Code.srt
- 6.95 KB
1. Introduction.srt
- 4.45 KB
4. How to Succeed in this Course.srt
- 4.36 KB
[Tutorialsplanet.NET].url
- 128 B
3. High Level Overview of Reinforcement Learning
1. What is Reinforcement Learning.mp4
- 54.63 MB
3. From Bandits to Full Reinforcement Learning.mp4
- 41.19 MB
2. On Unusual or Unexpected Strategies of RL.mp4
- 37.1 MB
3. From Bandits to Full Reinforcement Learning.srt
- 13.32 KB
1. What is Reinforcement Learning.srt
- 11.86 KB
2. On Unusual or Unexpected Strategies of RL.srt
- 8.57 KB
13. Appendix FAQ
2. BONUS Where to get discount coupons and FREE deep learning material.mp4
- 37.84 MB
1. What is the Appendix.mp4
- 5.46 MB
2. BONUS Where to get discount coupons and FREE deep learning material.srt
- 8.26 KB
1. What is the Appendix.srt
- 3.84 KB
[Tutorialsplanet.NET].url
- 128 B
13. Appendix FAQ Finale
2. BONUS Where to get discount coupons and FREE deep learning material.mp4
- 37.83 MB
1. What is the Appendix.mp4
- 5.46 MB
2. BONUS Where to get discount coupons and FREE deep learning material.srt
- 7.87 KB
1. What is the Appendix.srt
- 3.72 KB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4
- 37.62 MB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4
- 29.32 MB
1. How to Succeed in this Course (Long Version).mp4
- 18.32 MB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt
- 23.04 KB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt
- 16.03 KB
1. How to Succeed in this Course (Long Version).srt
- 14.55 KB
8. Approximation Methods
9. Course Summary and Next Steps.mp4
- 13.24 MB
8. Semi-Gradient SARSA in Code.mp4
- 10.61 MB
6. TD(0) Semi-Gradient Prediction.mp4
- 8.35 MB
5. Monte Carlo Prediction with Approximation in Code.mp4
- 6.56 MB
2. Linear Models for Reinforcement Learning.mp4
- 6.47 MB
1. Approximation Intro.mp4
- 6.46 MB
3. Features.mp4
- 6.24 MB
7. Semi-Gradient SARSA.mp4
- 4.71 MB
4. Monte Carlo Prediction with Approximation.mp4
- 2.84 MB
9. Course Summary and Next Steps.srt
- 15.95 KB
1. Approximation Intro.srt
- 7.99 KB
2. Linear Models for Reinforcement Learning.srt
- 7.39 KB
3. Features.srt
- 6.94 KB
6. TD(0) Semi-Gradient Prediction.srt
- 6.36 KB
7. Semi-Gradient SARSA.srt
- 5.47 KB
8. Semi-Gradient SARSA in Code.srt
- 5.4 KB
5. Monte Carlo Prediction with Approximation in Code.srt
- 4.01 KB
4. Monte Carlo Prediction with Approximation.srt
- 2.49 KB
6. Monte Carlo
6. Monte Carlo Control in Code.mp4
- 10.18 MB
5. Monte Carlo Control.mp4
- 9.26 MB
2. Monte Carlo Policy Evaluation.mp4
- 8.75 MB
8. Monte Carlo Control without Exploring Starts in Code.mp4
- 8.05 MB
3. Monte Carlo Policy Evaluation in Code.mp4
- 7.91 MB
4. Policy Evaluation in Windy Gridworld.mp4
- 7.82 MB
9. Monte Carlo Summary.mp4
- 5.71 MB
1. Monte Carlo Intro.mp4
- 4.97 MB
7. Monte Carlo Control without Exploring Starts.mp4
- 4.62 MB
2. Monte Carlo Policy Evaluation.srt
- 10.84 KB
5. Monte Carlo Control.srt
- 10.24 KB
9. Monte Carlo Summary.srt
- 7.1 KB
3. Monte Carlo Policy Evaluation in Code.srt
- 6.12 KB
1. Monte Carlo Intro.srt
- 5.96 KB
6. Monte Carlo Control in Code.srt
- 5.83 KB
7. Monte Carlo Control without Exploring Starts.srt
- 5.53 KB
4. Policy Evaluation in Windy Gridworld.srt
- 5.3 KB
8. Monte Carlo Control without Exploring Starts in Code.srt
- 3.63 KB
[Tutorialsplanet.NET].url
- 128 B
7. Temporal Difference Learning
5. SARSA in Code.mp4
- 8.82 MB
4. SARSA.mp4
- 8.2 MB
2. TD(0) Prediction.mp4
- 5.82 MB
7. Q Learning in Code.mp4
- 5.42 MB
3. TD(0) Prediction in Code.mp4
- 5.32 MB
6. Q Learning.mp4
- 4.84 MB
8. TD Summary.mp4
- 3.95 MB
1. Temporal Difference Intro.mp4
- 2.72 MB
4. SARSA.srt
- 9.7 KB
2. TD(0) Prediction.srt
- 6.38 KB
6. Q Learning.srt
- 5.82 KB
5. SARSA in Code.srt
- 5.53 KB
8. TD Summary.srt
- 4.66 KB
3. TD(0) Prediction in Code.srt
- 3.97 KB
7. Q Learning in Code.srt
- 3.46 KB
1. Temporal Difference Intro.srt
- 3.33 KB
[Tutorialsplanet.NET].url
- 128 B
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InfoHash:
C696D2608401665CE2F793ADCD59775DC8BFD85A
Last updated:
Mar 13, 2022
File count:
220 B
File Category:
1
Tags:
tutorialsplanet, udemy, artificial, intelligence, reinforcement, learning, python
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