Udemy - Artificial Intelligence: Reinforcement Learning in Python...

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 4.1 GB
  • Uploaded By CourseClub
  • Downloads 372
  • Last checked 2 weeks ago
  • Date uploaded 4 years ago
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Infohash : F6C9C8F8252C94189C7E50D95E6A63A052EA073F



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

Files:

[GigaCourse.Com] Udemy - Artificial Intelligence - Reinforcement Learning in Python 0. Websites you may like
  • [CourseClub.ME].url (0.1 KB)
  • [GigaCourse.Com].url (0.0 KB)
1. Welcome
  • 1. Introduction-en_US.srt (4.0 KB)
  • 1. Introduction.mp4 (34.2 MB)
  • 2. Course Outline and Big Picture-en_US.srt (10.0 KB)
  • 2. Course Outline and Big Picture.mp4 (39.7 MB)
  • 3. External URLs.txt (0.1 KB)
  • 3. Where to get the Code-en_US.srt (6.1 KB)
  • 3. Where to get the Code.mp4 (22.7 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)
  • 5. Warmup-en_US.srt (18.1 KB)
  • 5. Warmup.mp4 (62.6 MB)
10. Stock Trading Project with Reinforcement Learning
  • 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)
  • 10. Stock Trading Project Discussion-en_US.srt (4.2 KB)
  • 10. Stock Trading Project Discussion.mp4 (15.8 MB)
  • 2. Stock Trading Project Section Introduction-en_US.srt (6.6 KB)
  • 2. Stock Trading Project Section Introduction.mp4 (26.8 MB)
  • 3. Data and Environment-en_US.srt (15.1 KB)
  • 3. Data and Environment.mp4 (52.0 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)
  • 5. Design of the Program-en_US.srt (8.2 KB)
  • 5. Design of the Program.mp4 (23.3 MB)
  • 6. Code pt 1-en_US.srt (9.3 KB)
  • 6. Code pt 1.mp4 (49.7 MB)
  • 7. Code pt 2-en_US.srt (11.3 KB)
  • 7. Code pt 2.mp4 (65.3 MB)
  • 8. Code pt 3-en_US.srt (5.2 KB)
  • 8. Code pt 3.mp4 (33.7 MB)
  • 9. Code pt 4-en_US.srt (7.9 KB)
  • 9. Code pt 4.mp4 (52.9 MB)
  • [CourseClub.Me].url (0.1 KB)
  • [GigaCourse.Com].url (0.0 KB)
11. Setting Up Your Environment (FAQ by Student Request)
  • 1. Windows-Focused Environment Setup 2018-en_US.srt (19.3 KB)
  • 1. Windows-Focused Environment Setup 2018.mp4 (186.4 MB)
  • 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)
12. Extra Help With Python Coding for Beginners (FAQ by Student Request)
  • 1. How to Code by Yourself (part 1)-en_US.srt (26.0 KB)
  • 1. How to Code by Yourself (part 1).mp4 (24.5 MB)
  • 2. How to Code by Yourself (part 2)-en_US.srt (15.8 KB)
  • 2. How to Code by Yourself (part 2).mp4 (14.8 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)
  • 4. Python 2 vs Python 3-en_US.srt (5.9 KB)
  • 4. Python 2 vs Python 3.mp4 (7.8 MB)
13. Effective Learning Strategies for Machine Learning (FAQ by Student Request)
  • 1. How to Succeed in this Course (Long Version)-en_US.srt (14.0 KB)
  • 1. How to Succeed in this Course (Long Version).mp4 (18.3 MB)
  • 2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 (39.0 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)
  • 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)
14. Appendix FAQ Finale
  • 1. What is the Appendix-en_US.srt (3.6 KB)
  • 1. What is the Appendix.mp4 (5.5 MB)
  • 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. Return of the Multi-Armed Bandit
  • 1. Section Introduction The Explore-Exploit Dilemma-en_US.srt (13.0 KB)
  • 1. Section Introduction The Explore-Exploit Dilemma.mp4 (52.0 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)
  • 11. Optimistic Initial Values Code-en_US.srt (5.0 KB)
  • 11. Optimistic Initial Values Code.mp4 (24.6 MB)
  • 12. UCB1 Theory-en_US.srt (19.2 KB)
  • 12. UCB1 Theory.mp4 (55.5 MB)
  • 13. UCB1 Beginner's Exercise Prompt-en_US.srt (2.6 KB)
  • 13. UCB1 Beginner's Exercise Prompt.mp4 (12.7 MB)
  • 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)
  • 2. Applications of the Explore-Exploit Dilemma.mp4 (51.2 MB)
  • 20. Thompson Sampling With Gaussian Reward Code-en_US.srt (7.0 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 (31.0 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. Epsilon-Greedy Theory-en_US.srt (9.1 KB)
  • 3. Epsilon-Greedy Theory.mp4 (28.3 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)
  • 5. Epsilon-Greedy Beginner's Exercise Prompt-en_US.srt (6.2 KB)
  • 5. Epsilon-Greedy Beginner's Exercise Prompt.mp4 (28.7 MB)
  • 6. Designing Your Bandit Program-en_US.srt (5.4 KB)
  • 6. Designing Your Bandit Program.mp4 (24.5 MB)
  • 7. Epsilon-Greedy in Code-en_US.srt (8.3 KB)
  • 7. Epsilon-Greedy in Code.mp4 (41.4 MB)
  • 8. Comparing Different Epsilons-en_US.srt (6.5 KB)
  • 8. Comparing Different Epsilons.mp4 (43.7 MB)
  • 9. Optimistic Initial Values Theory-en_US.srt (6.9 KB)
  • 9. Optimistic Initial Values Theory.mp4 (23.5 MB)
3. High Level Overview of Reinforcement Learning
  • 1. What is Reinforcement Learning-en_US.srt (10.5 KB)
  • 1. What is Reinforcement Learning.mp4 (54.6 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)
  • [CourseClub.Me].url (0.1 KB)
  • [GigaCourse.Com].url (0.0 KB)
4. Markov Decision Proccesses
  • 1. MDP Section Introduction-en_US.srt (8.0 KB)
  • 1. MDP Section Introduction.mp4 (37.2 MB)
  • 10. The Bellman Equation (pt 3)-en_US.srt (7.4 KB)
  • 10. The Bellman Equation (pt 3).mp4 (24.7 MB)
  • 11. Bellman Examples-en_US.srt (26.6 KB)
  • 11. Bellman Examples.mp4 (87.1 MB)
  • 12. Optimal Policy and Optimal Value Function (pt 1)-en_US.srt (11.0 KB)
  • 12. Optimal Policy and Optimal Value Function (pt 1).mp4 (56.1 MB)
  • 13. Optimal Policy and Optimal Value Function (pt 2)-en_US.srt (4.9 KB)
  • 13. Optimal Policy and Optimal Value Function (pt 2).mp4 (15.7 MB)
  • 14. MDP Summary-en_US.srt (3.5 KB)
  • 14. MDP Summary.mp4 (14.3 MB)
  • 2. Gridworld-en_US.srt (16.6 KB)
  • 2. Gridworld.mp4 (54.0 MB)
  • 3. Choosing Rewards-en_US.srt (5.2 KB)
  • 3. Choosing Rewards.mp4 (32.5 MB)
  • 4. The Markov Property-en_US.srt (7.7 KB)
  • 4. The Markov Property.mp4 (21.8 MB)
  • 5. Markov Decision Processes (MDPs)-en_US.srt (18.8 KB)
  • 5. Markov Decision Processes (MDPs).mp4 (61.7 MB)
  • 6. Future Rewards-en_US.srt (12.2 KB)
  • 6. Future Rewards.mp4 (39.5 MB)
  • 7. Value Functions-en_US.srt (6.4 KB)
  • 7. Value Functions.mp4 (18.5 MB)
  • 8. The Bellman Equation (pt 1)-en_US.srt (10.7 KB)
  • 8. The Bellman Equation (pt 1).mp4 (27.8 MB)
  • 9. The Bellman Equation (pt 2)-en_US.srt (8.2 KB)
  • 9. The Bellman Equation (pt 2).mp4 (26.7 MB)
5. Dynamic Programming
  • 1. Dynamic Programming Section Introduction-en_US.srt (11.9 KB)
  • 1. Dynamic Programming Section Introduction.mp4 (34.7 MB)
  • 10. Policy Iteration in Code-en_US.srt (10.4 KB)
  • 10. Policy Iteration in Code.mp4 (56.4 MB)
  • 11. Policy Iteration in Windy Gridworld-en_US.srt (10.6 KB)
  • 11. Policy Iteration in Windy Gridworld.mp4 (51.4 MB)
  • 12. Value Iteration-en_US.srt (9.3 KB)
  • 12. Value Iteration.mp4 (35.3 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)
  • 2. Iterative Policy Evaluation-en_US.srt (20.4 KB)
  • 2. Iterative Policy Evaluation.mp4 (60.8 MB)
  • 3. Designing Your RL Program-en_US.srt (6.4 KB)
  • 3. Designing Your RL Program.mp4 (22.3 MB)
  • 4. Gridworld in Code-en_US.srt (15.7 KB)
  • 4. Gridworld in Code.mp4 (46.8 MB)
  • 5. Iterative Policy Evaluation in Code-en_US.srt (15.6 KB)
  • 5. Iterative Policy Evaluation in Code.mp4 (68.4 MB)
  • 6. Windy Gridworld in Code-en_US.srt (10.0 KB)
  • 6. Windy Gridworld in Code.mp4 (41.5 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)
  • 8. Policy Improvement-en_US.srt (14.2 KB)
  • 8. Policy Improvement.mp4 (44.0 MB)
  • 9. Policy Iteration-en_US.srt (10.0 KB)
  • 9. Policy Iteration.mp4 (34.2 MB)
6. Monte Carlo
  • 1. Monte Carlo Intro-en_US.srt (12.1 KB)
  • 1. Monte Carlo Intro.mp4 (47.6 MB)
  • 2. Monte Carlo Policy Evaluation-en_US.srt (14.1 KB)
  • 2. Monte Carlo Policy Evaluation.mp4 (47.1 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)
  • 4. Monte Carlo Control-en_US.srt (11.2 KB)
  • 4. Monte Carlo Control.mp4 (35.6 MB)
  • 5. Monte Carlo Control in Code-en_US.srt (10.7 KB)
  • 5. Monte Carlo Control in Code.mp4 (64.4 MB)
  • 6. Monte Carlo Control without Exploring Starts-en_US.srt (5.6 KB)
  • 6. Monte Carlo Control without Exploring Starts.mp4 (23.4 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)
  • 8. Monte Carlo Summary-en_US.srt (2.1 KB)
  • 8. Monte Carlo Summary.mp4 (11.4 MB)
7. Temporal Difference Learning
  • 1. Temporal Difference Introduction-en_US.srt (5.0 KB)
  • 1. Temporal Difference Introduction.mp4 (14.4 MB)
  • 2. TD(0) Prediction-en_US.srt (6.6 KB)
  • 2. TD(0) Prediction.mp4 (15.8 MB)
  • 3. TD(0) Prediction in Code-en_US.srt (5.8 KB)
  • 3. TD(0) Prediction in Code.mp4 (32.4 MB)
  • 4. SARSA-en_US.srt (5.8 KB)
  • 4. SARSA.mp4 (16.2 MB)
  • 5. SARSA in Code-en_US.srt (7.4 KB)
  • 5. SARSA in Code.mp4 (44.9 MB)
  • 6. Q Learning-en_US.srt (6.1 KB)
  • 6. Q Learning.mp4 (19.8 MB)
  • 7. Q Learning in Code-en_US.srt (5.8 KB)
  • 7. Q Learning in Code.mp4 (38.5 MB)
  • 8. TD Learning Section Summary-en_US.srt (2.9 KB)
  • 8. TD Learning Section Summary.mp4 (10.0 MB)
8. Approximation Methods
  • 1. Approximation Methods Section Introduction-en_US.srt (5.6 KB)
  • 1. Approximation Methods Section Introduction.mp4 (22.1 MB)
  • 10. Approximation Methods Exercise-en_US.srt (5.1 KB)
  • 10. Approximation Methods Exercise.mp4 (17.5 MB)
  • 11. Approximation Methods Section Summary-en_US.srt (3.8 KB)
  • 11. Approximation Methods Section Summary.mp4 (21.8 MB)
  • 2. Linear Models for Reinforcement Learning-en_US.srt (11.0 KB)
  • 2. Linear Models for Reinforcement Learning.mp4 (31.1 MB)
  • 3. Feature Engineering-en_US.srt (13.9 KB)
  • 3. Feature Engineering.mp4 (45.9 MB)
  • 4. Approximation Methods for Prediction-en_US.srt (12.1 KB)
  • 4. Approximation Methods for Prediction.mp4 (34.3 MB)
  • 5. Approximation Methods for Prediction Code-en_US.srt (10.2 KB)
  • 5. Approximation Methods for Prediction Code.mp4 (62.3 MB)
  • 6. Approximation Methods for Control-en_US.srt (5.5 KB)
  • 6. Approximation Methods for Control.mp4 (17.6 MB)
  • 7. Approximation Methods for Control Code-en_US.srt (10.5 KB)
  • 7. Approximation Methods for Control Code.mp4 (77.7 MB)
  • 8. CartPole-en_US.srt (7.0 KB)
  • 8. CartPole.mp4 (26.9 MB)
  • 9. CartPole Code-en_US.srt (6.5 KB)
  • 9. CartPole Code.mp4 (46.8 MB)
9. Interlude Common Beginner Questions
  • 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)
  • [CourseClub.Me].url (0.1 KB)
  • [GigaCourse.Com].url (0.0 KB)

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