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[FreeCourseLab.com] Udemy - Artificial Intelligence Reinforcement Learning in Python
magnet:?xt=urn:btih:0ce32fe1a70101bcfd8bd50d5a328e43f05f4f90&dn=[FreeCourseLab.com] Udemy - Artificial Intelligence Reinforcement Learning in Python
磁力链接详情
Hash值:
0ce32fe1a70101bcfd8bd50d5a328e43f05f4f90
点击数:
126
文件大小:
1.46 GB
文件数量:
88
创建日期:
2019-6-7 06:29
最后访问:
2024-11-6 11:35
访问标签:
FreeCourseLab
com
Udemy
-
Artificial
Intelligence
Reinforcement
Learning
in
Python
文件列表详情
1. Welcome/1. Introduction.mp4 34.25 MB
1. Welcome/2. Where to get the Code.mp4 4.46 MB
1. Welcome/3. Strategy for Passing the Course.mp4 9.47 MB
10. Appendix/1. What is the Appendix.mp4 5.46 MB
10. Appendix/10. What order should I take your courses in (part 1).mp4 29.32 MB
10. Appendix/11. What order should I take your courses in (part 2).mp4 37.62 MB
10. Appendix/12. Where to get discount coupons and FREE deep learning material.mp4 4.03 MB
10. Appendix/2. Windows-Focused Environment Setup 2018.mp4 186.39 MB
10. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.92 MB
10. Appendix/4. How to Code by Yourself (part 1).mp4 24.53 MB
10. Appendix/5. How to Code by Yourself (part 2).mp4 14.8 MB
10. Appendix/6. How to Succeed in this Course (Long Version).mp4 18.32 MB
10. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 38.96 MB
10. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4 78.32 MB
10. Appendix/9. Python 2 vs Python 3.mp4 7.84 MB
2. High Level Overview of Reinforcement Learning and Course Outline/1. What is Reinforcement Learning.mp4 54.62 MB
2. High Level Overview of Reinforcement Learning and Course Outline/2. On Unusual or Unexpected Strategies of RL.mp4 37.1 MB
2. High Level Overview of Reinforcement Learning and Course Outline/3. Course Outline.mp4 30.98 MB
2. High Level Overview of Reinforcement Learning and Course Outline/4. Defining Some Terms.mp4 42.34 MB
3. Return of the Multi-Armed Bandit/1. Problem Setup and The Explore-Exploit Dilemma.mp4 6.48 MB
3. Return of the Multi-Armed Bandit/10. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4 10.58 MB
3. Return of the Multi-Armed Bandit/11. Nonstationary Bandits.mp4 7.49 MB
3. Return of the Multi-Armed Bandit/2. Applications of the Explore-Exploit Dilemma.mp4 51.19 MB
3. Return of the Multi-Armed Bandit/3. Epsilon-Greedy.mp4 2.79 MB
3. Return of the Multi-Armed Bandit/4. Updating a Sample Mean.mp4 2.18 MB
3. Return of the Multi-Armed Bandit/5. Designing Your Bandit Program.mp4 24.52 MB
3. Return of the Multi-Armed Bandit/6. Comparing Different Epsilons.mp4 8.02 MB
3. Return of the Multi-Armed Bandit/7. Optimistic Initial Values.mp4 5.13 MB
3. Return of the Multi-Armed Bandit/8. UCB1.mp4 8.23 MB
3. Return of the Multi-Armed Bandit/9. Bayesian Thompson Sampling.mp4 51.85 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 8.31 MB
4. Build an Intelligent Tic-Tac-Toe Agent/12. Tic Tac Toe Exercise.mp4 19.78 MB
4. Build an Intelligent Tic-Tac-Toe Agent/2. Components of a Reinforcement Learning System.mp4 12.72 MB
4. Build an Intelligent Tic-Tac-Toe Agent/3. Notes on Assigning Rewards.mp4 4.23 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 4.43 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 7.19 MB
5. Markov Decision Proccesses/3. Defining and Formalizing the MDP.mp4 6.64 MB
5. Markov Decision Proccesses/4. Future Rewards.mp4 5.18 MB
5. Markov Decision Proccesses/5. Value Function Introduction.mp4 19.73 MB
5. Markov Decision Proccesses/6. Value Functions.mp4 8.28 MB
5. Markov Decision Proccesses/7. Bellman Examples.mp4 87.12 MB
5. Markov Decision Proccesses/8. Optimal Policy and Optimal Value Function.mp4 3.24 MB
5. Markov Decision Proccesses/9. MDP Summary.mp4 2.42 MB
6. Dynamic Programming/1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4 4.84 MB
6. Dynamic Programming/10. Value Iteration in Code.mp4 4.89 MB
6. Dynamic Programming/11. Dynamic Programming Summary.mp4 8.32 MB
6. Dynamic Programming/2. Gridworld in Code.mp4 11.47 MB
6. Dynamic Programming/3. Designing Your RL Program.mp4 22.35 MB
6. Dynamic Programming/4. Iterative Policy Evaluation in Code.mp4 12.07 MB
6. Dynamic Programming/5. Policy Improvement.mp4 4.53 MB
6. Dynamic Programming/6. Policy Iteration.mp4 3.13 MB
6. Dynamic Programming/7. Policy Iteration in Code.mp4 7.62 MB
6. Dynamic Programming/8. Policy Iteration in Windy Gridworld.mp4 9.11 MB
6. Dynamic Programming/9. Value Iteration.mp4 6.19 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 7.82 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 4.63 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 5.72 MB
8. Temporal Difference Learning/1. Temporal Difference Intro.mp4 2.73 MB
8. Temporal Difference Learning/2. TD(0) Prediction.mp4 5.83 MB
8. Temporal Difference Learning/3. TD(0) Prediction in Code.mp4 5.33 MB
8. Temporal Difference Learning/4. SARSA.mp4 8.21 MB
8. Temporal Difference Learning/5. SARSA in Code.mp4 8.82 MB
8. Temporal Difference Learning/6. Q Learning.mp4 4.85 MB
8. Temporal Difference Learning/7. Q Learning in Code.mp4 5.43 MB
8. Temporal Difference Learning/8. TD Summary.mp4 3.95 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 6.24 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 13.25 MB
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