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[DesireCourse.Net] Udemy - Artificial Intelligence Reinforcement Learning in Python
magnet:?xt=urn:btih:186fe32040da9247b2eeaf42415f6d0019895524&dn=[DesireCourse.Net] Udemy - Artificial Intelligence Reinforcement Learning in Python
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文件列表详情
186fe32040da9247b2eeaf42415f6d0019895524
infohash:
98
文件数量
1.9 GB
文件大小
2020-10-30 09:16
创建日期
2024-7-14 15:26
最后访问
相关分词
DesireCourse
Net
Udemy
-
Artificial
Intelligence
Reinforcement
Learning
in
Python
1. Welcome/1. Introduction.mp4 34.24 MB
1. Welcome/2. Where to get the Code.mp4 4.45 MB
1. Welcome/3. Strategy for Passing the Course.mp4 9.48 MB
1. Welcome/4. Course Outline.mp4 30.97 MB
10. Stock Trading Project with Reinforcement Learning/1. Stock Trading Project Section Introduction.mp4 26.77 MB
10. Stock Trading Project with Reinforcement Learning/2. Data and Environment.mp4 52.01 MB
10. Stock Trading Project with Reinforcement Learning/3. How to Model Q for Q-Learning.mp4 44.89 MB
10. Stock Trading Project with Reinforcement Learning/4. Design of the Program.mp4 23.31 MB
10. Stock Trading Project with Reinforcement Learning/5. Code pt 1.mp4 49.72 MB
10. Stock Trading Project with Reinforcement Learning/6. Code pt 2.mp4 65.29 MB
10. Stock Trading Project with Reinforcement Learning/7. Code pt 3.mp4 33.72 MB
10. Stock Trading Project with Reinforcement Learning/8. Code pt 4.mp4 49.08 MB
10. Stock Trading Project with Reinforcement Learning/9. Stock Trading Project Discussion.mp4 15.78 MB
11. Appendix FAQ/1. What is the Appendix.mp4 5.45 MB
11. Appendix FAQ/10. What order should I take your courses in (part 1).mp4 29.32 MB
11. Appendix FAQ/11. What order should I take your courses in (part 2).mp4 37.62 MB
11. Appendix FAQ/12. BONUS Where to get discount coupons and FREE deep learning material.mp4 37.83 MB
11. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4 186.38 MB
11. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.92 MB
11. Appendix FAQ/4. How to Code by Yourself (part 1).mp4 24.54 MB
11. Appendix FAQ/5. How to Code by Yourself (part 2).mp4 14.8 MB
11. Appendix FAQ/6. How to Succeed in this Course (Long Version).mp4 18.31 MB
11. Appendix FAQ/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 38.95 MB
11. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.mp4 78.32 MB
11. Appendix FAQ/9. Python 2 vs Python 3.mp4 7.84 MB
2. Return of the Multi-Armed Bandit/1. Problem Setup and The Explore-Exploit Dilemma.mp4 6.47 MB
2. Return of the Multi-Armed Bandit/10. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4 10.57 MB
2. Return of the Multi-Armed Bandit/11. Nonstationary Bandits.mp4 7.48 MB
2. Return of the Multi-Armed Bandit/12. Bandit Summary, Real Data, and Online Learning.mp4 33.92 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/3. Epsilon-Greedy.mp4 2.78 MB
2. Return of the Multi-Armed Bandit/4. Updating a Sample Mean.mp4 2.18 MB
2. Return of the Multi-Armed Bandit/5. Designing Your Bandit Program.mp4 24.51 MB
2. Return of the Multi-Armed Bandit/6. Comparing Different Epsilons.mp4 8.01 MB
2. Return of the Multi-Armed Bandit/7. Optimistic Initial Values.mp4 15.84 MB
2. Return of the Multi-Armed Bandit/8. UCB1.mp4 8.23 MB
2. Return of the Multi-Armed Bandit/9. Bayesian Thompson Sampling.mp4 51.85 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. On Unusual or Unexpected Strategies of RL.mp4 37.1 MB
3. High Level Overview of Reinforcement Learning/3. Defining Some Terms.mp4 42.34 MB
4. Build an Intelligent Tic-Tac-Toe Agent/1. Naive Solution to Tic-Tac-Toe.mp4 6.12 MB
4. Build an Intelligent Tic-Tac-Toe Agent/10. Tic Tac Toe Code Main Loop and Demo.mp4 9.44 MB
4. Build an Intelligent Tic-Tac-Toe Agent/11. Tic Tac Toe Summary.mp4 8.32 MB
4. Build an Intelligent Tic-Tac-Toe Agent/12. Tic Tac Toe Exercise.mp4 19.77 MB
4. Build an Intelligent Tic-Tac-Toe Agent/2. Components of a Reinforcement Learning System.mp4 12.71 MB
4. Build an Intelligent Tic-Tac-Toe Agent/3. Notes on Assigning Rewards.mp4 4.22 MB
4. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.mp4 103.72 MB
4. Build an Intelligent Tic-Tac-Toe Agent/5. Tic Tac Toe Code Outline.mp4 5.04 MB
4. Build an Intelligent Tic-Tac-Toe Agent/6. Tic Tac Toe Code Representing States.mp4 4.42 MB
4. Build an Intelligent Tic-Tac-Toe Agent/7. Tic Tac Toe Code Enumerating States Recursively.mp4 9.79 MB
4. Build an Intelligent Tic-Tac-Toe Agent/8. Tic Tac Toe Code The Environment.mp4 10.05 MB
4. Build an Intelligent Tic-Tac-Toe Agent/9. Tic Tac Toe Code The Agent.mp4 9.01 MB
5. Markov Decision Proccesses/1. Gridworld.mp4 3.36 MB
5. Markov Decision Proccesses/2. The Markov Property.mp4 7.18 MB
5. Markov Decision Proccesses/3. Defining and Formalizing the MDP.mp4 6.64 MB
5. Markov Decision Proccesses/4. Future Rewards.mp4 5.17 MB
5. Markov Decision Proccesses/5. Value Function Introduction.mp4 19.72 MB
5. Markov Decision Proccesses/6. Value Functions.mp4 8.29 MB
5. Markov Decision Proccesses/7. Bellman Examples.mp4 87.12 MB
5. Markov Decision Proccesses/8. Optimal Policy and Optimal Value Function.mp4 3.23 MB
5. Markov Decision Proccesses/9. MDP Summary.mp4 5.67 MB
6. Dynamic Programming/1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4 4.83 MB
6. Dynamic Programming/10. Value Iteration in Code.mp4 4.89 MB
6. Dynamic Programming/11. Dynamic Programming Summary.mp4 8.31 MB
6. Dynamic Programming/2. Gridworld in Code.mp4 11.46 MB
6. Dynamic Programming/3. Designing Your RL Program.mp4 22.34 MB
6. Dynamic Programming/4. Iterative Policy Evaluation in Code.mp4 12.06 MB
6. Dynamic Programming/5. Policy Improvement.mp4 4.53 MB
6. Dynamic Programming/6. Policy Iteration.mp4 3.14 MB
6. Dynamic Programming/7. Policy Iteration in Code.mp4 7.62 MB
6. Dynamic Programming/8. Policy Iteration in Windy Gridworld.mp4 9.1 MB
6. Dynamic Programming/9. Value Iteration.mp4 6.18 MB
7. Monte Carlo/1. Monte Carlo Intro.mp4 4.97 MB
7. Monte Carlo/2. Monte Carlo Policy Evaluation.mp4 8.75 MB
7. Monte Carlo/3. Monte Carlo Policy Evaluation in Code.mp4 7.92 MB
7. Monte Carlo/4. Policy Evaluation in Windy Gridworld.mp4 7.81 MB
7. Monte Carlo/5. Monte Carlo Control.mp4 9.26 MB
7. Monte Carlo/6. Monte Carlo Control in Code.mp4 10.17 MB
7. Monte Carlo/7. Monte Carlo Control without Exploring Starts.mp4 4.62 MB
7. Monte Carlo/8. Monte Carlo Control without Exploring Starts in Code.mp4 8.06 MB
7. Monte Carlo/9. Monte Carlo Summary.mp4 5.71 MB
8. Temporal Difference Learning/1. Temporal Difference Intro.mp4 2.73 MB
8. Temporal Difference Learning/2. TD(0) Prediction.mp4 5.82 MB
8. Temporal Difference Learning/3. TD(0) Prediction in Code.mp4 5.32 MB
8. Temporal Difference Learning/4. SARSA.mp4 8.2 MB
8. Temporal Difference Learning/5. SARSA in Code.mp4 8.82 MB
8. Temporal Difference Learning/6. Q Learning.mp4 4.84 MB
8. Temporal Difference Learning/7. Q Learning in Code.mp4 5.42 MB
8. Temporal Difference Learning/8. TD Summary.mp4 3.94 MB
9. Approximation Methods/1. Approximation Intro.mp4 6.47 MB
9. Approximation Methods/2. Linear Models for Reinforcement Learning.mp4 6.47 MB
9. Approximation Methods/3. Features.mp4 6.25 MB
9. Approximation Methods/4. Monte Carlo Prediction with Approximation.mp4 2.85 MB
9. Approximation Methods/5. Monte Carlo Prediction with Approximation in Code.mp4 6.57 MB
9. Approximation Methods/6. TD(0) Semi-Gradient Prediction.mp4 8.36 MB
9. Approximation Methods/7. Semi-Gradient SARSA.mp4 4.7 MB
9. Approximation Methods/8. Semi-Gradient SARSA in Code.mp4 10.61 MB
9. Approximation Methods/9. Course Summary and Next Steps.mp4 13.24 MB
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