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种子名称： [DesireCourse.Net] Udemy - Advanced AI Deep Reinforcement Learning in Python
文件类型： 视频
文件数目： 73个文件
文件大小： 2.28 GB
收录时间： 2020-1-13 18:44
已经下载： 3次
资源热度： 167
最近下载： 2024-11-13 11:39

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[DesireCourse.Net] Udemy - Advanced AI Deep Reinforcement Learning in Python.torrent

1. Introduction and Logistics/1. Introduction and Outline.mp415.84MB

1. Introduction and Logistics/2. Where to get the Code.mp45.19MB

1. Introduction and Logistics/3. How to Succeed in this Course.mp43.3MB

1. Introduction and Logistics/4. Tensorflow or Theano - Your Choice!.mp418.93MB

2. Background Review/1. Review Intro.mp44.2MB

2. Background Review/2. Review of Markov Decision Processes.mp412.3MB

2. Background Review/3. Review of Dynamic Programming.mp46.52MB

2. Background Review/4. Review of Monte Carlo Methods.mp46.18MB

2. Background Review/5. Review of Temporal Difference Learning.mp418.52MB

2. Background Review/6. Review of Approximation Methods for Reinforcement Learning.mp43.67MB

2. Background Review/7. Review of Deep Learning.mp411.05MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/1. OpenAI Gym Tutorial.mp48.67MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/10. Theano Warmup.mp45.83MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/11. Tensorflow Warmup.mp45.06MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/12. Plugging in a Neural Network.mp45.92MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/13. OpenAI Gym Section Summary.mp45.32MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/2. Random Search.mp410.29MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/3. Saving a Video.mp44.55MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/4. CartPole with Bins (Theory).mp46.02MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/5. CartPole with Bins (Code).mp414.7MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/6. RBF Neural Networks.mp416.51MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/7. RBF Networks with Mountain Car (Code).mp413.76MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/8. RBF Networks with CartPole (Theory).mp43.06MB

3. OpenAI Gym and Basic Reinforcement Learning Techniques/9. RBF Networks with CartPole (Code).mp48.92MB

4. TD Lambda/1. N-Step Methods.mp45.03MB

4. TD Lambda/2. N-Step in Code.mp49.47MB

4. TD Lambda/3. TD Lambda.mp411.77MB

4. TD Lambda/4. TD Lambda in Code.mp47.63MB

4. TD Lambda/5. TD Lambda Summary.mp43.65MB

5. Policy Gradients/1. Policy Gradient Methods.mp417.94MB

5. Policy Gradients/10. Policy Gradient Section Summary.mp43.33MB

5. Policy Gradients/2. Policy Gradient in TensorFlow for CartPole.mp417.97MB

5. Policy Gradients/3. Policy Gradient in Theano for CartPole.mp413.44MB

5. Policy Gradients/4. Continuous Action Spaces.mp46.59MB

5. Policy Gradients/5. Mountain Car Continuous Specifics.mp46.51MB

5. Policy Gradients/6. Mountain Car Continuous Theano.mp419.06MB

5. Policy Gradients/7. Mountain Car Continuous Tensorflow.mp420.09MB

5. Policy Gradients/8. Mountain Car Continuous Tensorflow (v2).mp418.78MB

5. Policy Gradients/9. Mountain Car Continuous Theano (v2).mp422.19MB

6. Deep Q-Learning/1. Deep Q-Learning Intro.mp45.9MB

6. Deep Q-Learning/10. Deep Q-Learning Section Summary.mp410.4MB

6. Deep Q-Learning/2. Deep Q-Learning Techniques.mp414.44MB

6. Deep Q-Learning/3. Deep Q-Learning in Tensorflow for CartPole.mp414.98MB

6. Deep Q-Learning/4. Deep Q-Learning in Theano for CartPole.mp413.76MB

6. Deep Q-Learning/5. Additional Implementation Details for Atari.mp48.51MB

6. Deep Q-Learning/6. Pseudocode and Replay Memory.mp427.81MB

6. Deep Q-Learning/7. Deep Q-Learning in Tensorflow for Breakout.mp4234.6MB

6. Deep Q-Learning/8. Deep Q-Learning in Theano for Breakout.mp4233.69MB

6. Deep Q-Learning/9. Partially Observable MDPs.mp47.61MB

7. A3C/1. A3C - Theory and Outline.mp471.76MB

7. A3C/2. A3C - Code pt 1 (Warmup).mp450.09MB

7. A3C/3. A3C - Code pt 2.mp457.61MB

7. A3C/4. A3C - Code pt 3.mp484.52MB

7. A3C/5. A3C - Code pt 4.mp4184.34MB

7. A3C/6. A3C - Section Summary.mp48.85MB

7. A3C/7. Course Summary.mp49.45MB

8. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp493.41MB

8. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp487.01MB

8. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp481.42MB

8. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp497.29MB

9. Appendix FAQ/1. What is the Appendix.mp45.45MB

9. Appendix FAQ/10. Is Theano Dead.mp417.81MB

9. Appendix FAQ/11. What order should I take your courses in (part 1).mp429.32MB

9. Appendix FAQ/12. What order should I take your courses in (part 2).mp437.62MB

9. Appendix FAQ/13. BONUS Where to get Udemy coupons and FREE deep learning material.mp437.84MB

9. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4186.16MB

9. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB

9. Appendix FAQ/4. How to Code by Yourself (part 1).mp424.53MB

9. Appendix FAQ/5. How to Code by Yourself (part 2).mp414.8MB

9. Appendix FAQ/6. How to Succeed in this Course (Long Version).mp418.31MB

9. Appendix FAQ/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.95MB

9. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.mp478.24MB

9. Appendix FAQ/9. Python 2 vs Python 3.mp47.83MB