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[FreeTutorials.Us] [UDEMY] Cutting-Edge AI Deep Reinforcement Learning in Python [FTU]

Torrent Hash :
9d445aaf0fff5ffe5c45caafd66e692781faf725
Content Size :
3.31 GB
Date :
2019-09-07
Short Magnet :
Short Magnet
https://0mag.biz/!QEO6A9 QR code
Files ( 102 )size
6. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4194.34 MB
4. DDPG (Deep Deterministic Policy Gradient)/5. DDPG Code (part 1).mp4193.58 MB
3. A2C (Advantage Actor-Critic)/10. A2C.mp4192.28 MB
6. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4167.01 MB
5. ES (Evolution Strategies)/7. ES for Flappy Bird in Code.mp4142.23 MB
6. Appendix FAQ/11. What order should I take your courses in (part 2).mp4139.37 MB
3. A2C (Advantage Actor-Critic)/8. Environment Wrappers.mp4128.58 MB
6. Appendix FAQ/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4117.54 MB
4. DDPG (Deep Deterministic Policy Gradient)/4. MuJoCo.mp4110.45 MB
2. Review of Fundamental Reinforcement Learning Concepts/3. Markov Decision Processes (MDPs).mp4108.66 MB
5. ES (Evolution Strategies)/2. ES Theory.mp4108.21 MB
6. Appendix FAQ/10. What order should I take your courses in (part 1).mp499.39 MB
3. A2C (Advantage Actor-Critic)/2. A2C Theory (part 1).mp496.21 MB
6. Appendix FAQ/6. How to Code by Yourself (part 1).mp482.57 MB
4. DDPG (Deep Deterministic Policy Gradient)/3. DDPG Theory.mp480.68 MB
2. Review of Fundamental Reinforcement Learning Concepts/5. Temporal Difference Learning (TD).mp478.57 MB
6. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.mp478.27 MB
2. Review of Fundamental Reinforcement Learning Concepts/2. The Explore-Exploit Dilemma.mp471.63 MB
3. A2C (Advantage Actor-Critic)/7. Multiple Processes.mp470.09 MB
5. ES (Evolution Strategies)/8. ES for MuJoCo in Code.mp468.63 MB
4. DDPG (Deep Deterministic Policy Gradient)/6. DDPG Code (part 2).mp464.82 MB
3. A2C (Advantage Actor-Critic)/1. A2C Section Introduction.mp461.3 MB
5. ES (Evolution Strategies)/6. Flappy Bird.mp460.92 MB
6. Appendix FAQ/7. How to Code by Yourself (part 2).mp456.7 MB
5. ES (Evolution Strategies)/5. ES for Supervised Learning.mp455.16 MB
1. Welcome/2. Outline.mp454.25 MB
5. ES (Evolution Strategies)/3. Notes on Evolution Strategies.mp453.1 MB
2. Review of Fundamental Reinforcement Learning Concepts/6. OpenAI Gym Warmup.mp449.72 MB
5. ES (Evolution Strategies)/4. ES for Optimizing a Function.mp446.51 MB
3. A2C (Advantage Actor-Critic)/9. Convolutional Neural Network.mp445.66 MB
4. DDPG (Deep Deterministic Policy Gradient)/2. Deep Q-Learning (DQN) Review.mp445.16 MB
5. ES (Evolution Strategies)/1. ES Section Introduction.mp444.86 MB
6. Appendix FAQ/5. How to Succeed in this Course (Long Version).mp439.26 MB
3. A2C (Advantage Actor-Critic)/11. A2C Section Summary.mp432.72 MB
3. A2C (Advantage Actor-Critic)/3. A2C Theory (part 2).mp432.59 MB
2. Review of Fundamental Reinforcement Learning Concepts/4. Monte Carlo Methods.mp432.07 MB
2. Review of Fundamental Reinforcement Learning Concepts/7. Review Section Summary.mp431.17 MB
1. Welcome/1. Introduction.mp429.55 MB
5. ES (Evolution Strategies)/9. ES Section Summary.mp428.64 MB
3. A2C (Advantage Actor-Critic)/6. A2C Code - Rough Sketch.mp428.49 MB
3. A2C (Advantage Actor-Critic)/5. A2C Demo.mp427.42 MB
1. Welcome/3. Where to get the code.mp424.45 MB
4. DDPG (Deep Deterministic Policy Gradient)/1. DDPG Section Introduction.mp423.92 MB
6. Appendix FAQ/9. Python 2 vs Python 3.mp418.98 MB
2. Review of Fundamental Reinforcement Learning Concepts/1. Review Section Introduction.mp418.88 MB
6. Appendix FAQ/1. What is the Appendix.mp418.07 MB
4. DDPG (Deep Deterministic Policy Gradient)/7. DDPG Section Summary.mp417.6 MB
3. A2C (Advantage Actor-Critic)/4. A2C Theory (part 3).mp414.22 MB
6. Appendix FAQ/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt27.68 KB
3. A2C (Advantage Actor-Critic)/2. A2C Theory (part 1).vtt22.8 KB

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