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[FreeCourseSite.com] Udemy - Artificial Intelligence Reinforcement Learning in Python
magnet:?xt=urn:btih:f6ccac454514e2294c8b00762280187993fb3628&dn=[FreeCourseSite.com] Udemy - Artificial Intelligence Reinforcement Learning in Python
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Hash值:
f6ccac454514e2294c8b00762280187993fb3628
点击数:
180
文件大小:
4.13 GB
文件数量:
110
创建日期:
2021-7-10 08:31
最后访问:
2024-6-21 10:57
访问标签:
FreeCourseSite
com
Udemy
-
Artificial
Intelligence
Reinforcement
Learning
in
Python
文件列表详情
1. Welcome/1. Introduction.mp4 34.24 MB
1. Welcome/2. Course Outline and Big Picture.mp4 39.68 MB
1. Welcome/3. Where to get the Code.mp4 22.72 MB
1. Welcome/4. How to Succeed in this Course.mp4 43.82 MB
1. Welcome/5. Warmup.mp4 62.6 MB
10. Stock Trading Project with Reinforcement Learning/1. Beginners, halt! Stop here if you skipped ahead.mp4 83.78 MB
10. Stock Trading Project with Reinforcement Learning/10. Stock Trading Project Discussion.mp4 15.78 MB
10. Stock Trading Project with Reinforcement Learning/2. Stock Trading Project Section Introduction.mp4 26.76 MB
10. Stock Trading Project with Reinforcement Learning/3. Data and Environment.mp4 52.01 MB
10. Stock Trading Project with Reinforcement Learning/4. How to Model Q for Q-Learning.mp4 44.89 MB
10. Stock Trading Project with Reinforcement Learning/5. Design of the Program.mp4 23.31 MB
10. Stock Trading Project with Reinforcement Learning/6. Code pt 1.mp4 49.72 MB
10. Stock Trading Project with Reinforcement Learning/7. Code pt 2.mp4 65.29 MB
10. Stock Trading Project with Reinforcement Learning/8. Code pt 3.mp4 33.72 MB
10. Stock Trading Project with Reinforcement Learning/9. Code pt 4.mp4 52.94 MB
11. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 186.38 MB
11. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.92 MB
12. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4 24.53 MB
12. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).mp4 14.8 MB
12. 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 78.32 MB
12. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.mp4 7.83 MB
13. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).mp4 18.31 MB
13. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 38.95 MB
13. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 29.32 MB
13. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 37.62 MB
14. Appendix FAQ Finale/1. What is the Appendix.mp4 5.45 MB
14. Appendix FAQ Finale/2. BONUS Where to get discount coupons and FREE deep learning material.mp4 37.83 MB
2. Return of the Multi-Armed Bandit/1. Section Introduction The Explore-Exploit Dilemma.mp4 51.99 MB
2. Return of the Multi-Armed Bandit/10. Optimistic Initial Values Beginner's Exercise Prompt.mp4 13.77 MB
2. Return of the Multi-Armed Bandit/11. Optimistic Initial Values Code.mp4 24.57 MB
2. Return of the Multi-Armed Bandit/12. UCB1 Theory.mp4 55.53 MB
2. Return of the Multi-Armed Bandit/13. UCB1 Beginner's Exercise Prompt.mp4 12.74 MB
2. Return of the Multi-Armed Bandit/14. UCB1 Code.mp4 20.66 MB
2. Return of the Multi-Armed Bandit/15. Bayesian Bandits Thompson Sampling Theory (pt 1).mp4 55.9 MB
2. Return of the Multi-Armed Bandit/16. Bayesian Bandits Thompson Sampling Theory (pt 2).mp4 74.5 MB
2. Return of the Multi-Armed Bandit/17. Thompson Sampling Beginner's Exercise Prompt.mp4 17.89 MB
2. Return of the Multi-Armed Bandit/18. Thompson Sampling Code.mp4 32.83 MB
2. Return of the Multi-Armed Bandit/19. Thompson Sampling With Gaussian Reward Theory.mp4 48.51 MB
2. Return of the Multi-Armed Bandit/2. Applications of the Explore-Exploit Dilemma.mp4 51.18 MB
2. Return of the Multi-Armed Bandit/20. Thompson Sampling With Gaussian Reward Code.mp4 43.43 MB
2. Return of the Multi-Armed Bandit/21. Why don't we just use a library.mp4 27.4 MB
2. Return of the Multi-Armed Bandit/22. Nonstationary Bandits.mp4 30.98 MB
2. Return of the Multi-Armed Bandit/23. Bandit Summary, Real Data, and Online Learning.mp4 34.61 MB
2. Return of the Multi-Armed Bandit/24. (Optional) Alternative Bandit Designs.mp4 50.34 MB
2. Return of the Multi-Armed Bandit/25. Suggestion Box.mp4 16.13 MB
2. Return of the Multi-Armed Bandit/3. Epsilon-Greedy Theory.mp4 28.3 MB
2. Return of the Multi-Armed Bandit/4. Calculating a Sample Mean (pt 1).mp4 23.13 MB
2. Return of the Multi-Armed Bandit/5. Epsilon-Greedy Beginner's Exercise Prompt.mp4 28.66 MB
2. Return of the Multi-Armed Bandit/6. Designing Your Bandit Program.mp4 24.51 MB
2. Return of the Multi-Armed Bandit/7. Epsilon-Greedy in Code.mp4 41.43 MB
2. Return of the Multi-Armed Bandit/8. Comparing Different Epsilons.mp4 43.65 MB
2. Return of the Multi-Armed Bandit/9. Optimistic Initial Values Theory.mp4 23.52 MB
3. High Level Overview of Reinforcement Learning/1. What is Reinforcement Learning.mp4 54.62 MB
3. High Level Overview of Reinforcement Learning/2. From Bandits to Full Reinforcement Learning.mp4 41.19 MB
4. Markov Decision Proccesses/1. MDP Section Introduction.mp4 37.2 MB
4. Markov Decision Proccesses/10. The Bellman Equation (pt 3).mp4 24.67 MB
4. Markov Decision Proccesses/11. Bellman Examples.mp4 87.12 MB
4. Markov Decision Proccesses/12. Optimal Policy and Optimal Value Function (pt 1).mp4 56.06 MB
4. Markov Decision Proccesses/13. Optimal Policy and Optimal Value Function (pt 2).mp4 15.72 MB
4. Markov Decision Proccesses/14. MDP Summary.mp4 14.28 MB
4. Markov Decision Proccesses/2. Gridworld.mp4 53.99 MB
4. Markov Decision Proccesses/3. Choosing Rewards.mp4 32.49 MB
4. Markov Decision Proccesses/4. The Markov Property.mp4 21.76 MB
4. Markov Decision Proccesses/5. Markov Decision Processes (MDPs).mp4 61.73 MB
4. Markov Decision Proccesses/6. Future Rewards.mp4 39.5 MB
4. Markov Decision Proccesses/7. Value Functions.mp4 18.55 MB
4. Markov Decision Proccesses/8. The Bellman Equation (pt 1).mp4 27.78 MB
4. Markov Decision Proccesses/9. The Bellman Equation (pt 2).mp4 26.69 MB
5. Dynamic Programming/1. Dynamic Programming Section Introduction.mp4 34.67 MB
5. Dynamic Programming/10. Policy Iteration in Code.mp4 56.38 MB
5. Dynamic Programming/11. Policy Iteration in Windy Gridworld.mp4 51.41 MB
5. Dynamic Programming/12. Value Iteration.mp4 35.27 MB
5. Dynamic Programming/13. Value Iteration in Code.mp4 45.67 MB
5. Dynamic Programming/14. Dynamic Programming Summary.mp4 25.11 MB
5. Dynamic Programming/2. Iterative Policy Evaluation.mp4 60.82 MB
5. Dynamic Programming/3. Designing Your RL Program.mp4 22.34 MB
5. Dynamic Programming/4. Gridworld in Code.mp4 46.79 MB
5. Dynamic Programming/5. Iterative Policy Evaluation in Code.mp4 68.43 MB
5. Dynamic Programming/6. Windy Gridworld in Code.mp4 41.45 MB
5. Dynamic Programming/7. Iterative Policy Evaluation for Windy Gridworld in Code.mp4 46.93 MB
5. Dynamic Programming/8. Policy Improvement.mp4 43.99 MB
5. Dynamic Programming/9. Policy Iteration.mp4 34.15 MB
6. Monte Carlo/1. Monte Carlo Intro.mp4 47.59 MB
6. Monte Carlo/2. Monte Carlo Policy Evaluation.mp4 47.15 MB
6. Monte Carlo/3. Monte Carlo Policy Evaluation in Code.mp4 51.65 MB
6. Monte Carlo/4. Monte Carlo Control.mp4 35.61 MB
6. Monte Carlo/5. Monte Carlo Control in Code.mp4 64.41 MB
6. Monte Carlo/6. Monte Carlo Control without Exploring Starts.mp4 23.4 MB
6. Monte Carlo/7. Monte Carlo Control without Exploring Starts in Code.mp4 40.69 MB
6. Monte Carlo/8. Monte Carlo Summary.mp4 11.4 MB
7. Temporal Difference Learning/1. Temporal Difference Introduction.mp4 14.44 MB
7. Temporal Difference Learning/2. TD(0) Prediction.mp4 15.79 MB
7. Temporal Difference Learning/3. TD(0) Prediction in Code.mp4 32.43 MB
7. Temporal Difference Learning/4. SARSA.mp4 16.22 MB
7. Temporal Difference Learning/5. SARSA in Code.mp4 44.9 MB
7. Temporal Difference Learning/6. Q Learning.mp4 19.82 MB
7. Temporal Difference Learning/7. Q Learning in Code.mp4 38.55 MB
7. Temporal Difference Learning/8. TD Learning Section Summary.mp4 10.04 MB
8. Approximation Methods/1. Approximation Methods Section Introduction.mp4 22.08 MB
8. Approximation Methods/10. Approximation Methods Exercise.mp4 17.53 MB
8. Approximation Methods/11. Approximation Methods Section Summary.mp4 21.75 MB
8. Approximation Methods/2. Linear Models for Reinforcement Learning.mp4 31.08 MB
8. Approximation Methods/3. Feature Engineering.mp4 45.88 MB
8. Approximation Methods/4. Approximation Methods for Prediction.mp4 34.34 MB
8. Approximation Methods/5. Approximation Methods for Prediction Code.mp4 62.29 MB
8. Approximation Methods/6. Approximation Methods for Control.mp4 17.59 MB
8. Approximation Methods/7. Approximation Methods for Control Code.mp4 77.69 MB
8. Approximation Methods/8. CartPole.mp4 26.9 MB
8. Approximation Methods/9. CartPole Code.mp4 46.83 MB
9. Interlude Common Beginner Questions/1. This Course vs. RL Book What's the Difference.mp4 38.21 MB
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