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

•  6. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4  194.34 MB
•  4. DDPG (Deep Deterministic Policy Gradient)/5. DDPG Code (part 1).mp4  193.58 MB
•  3. A2C (Advantage Actor-Critic)/10. A2C.mp4  192.28 MB
•  6. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4  167.01 MB
•  5. ES (Evolution Strategies)/7. ES for Flappy Bird in Code.mp4  142.23 MB
•  6. Appendix FAQ/11. What order should I take your courses in (part 2).mp4  139.37 MB
•  3. A2C (Advantage Actor-Critic)/8. Environment Wrappers.mp4  128.58 MB
•  6. Appendix FAQ/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4  117.54 MB
•  4. DDPG (Deep Deterministic Policy Gradient)/4. MuJoCo.mp4  110.45 MB
•  2. Review of Fundamental Reinforcement Learning Concepts/3. Markov Decision Processes (MDPs).mp4  108.66 MB
•  5. ES (Evolution Strategies)/2. ES Theory.mp4  108.21 MB
•  6. Appendix FAQ/10. What order should I take your courses in (part 1).mp4  99.39 MB
•  3. A2C (Advantage Actor-Critic)/2. A2C Theory (part 1).mp4  96.21 MB
•  6. Appendix FAQ/6. How to Code by Yourself (part 1).mp4  82.57 MB
•  4. DDPG (Deep Deterministic Policy Gradient)/3. DDPG Theory.mp4  80.68 MB
•  2. Review of Fundamental Reinforcement Learning Concepts/5. Temporal Difference Learning (TD).mp4  78.57 MB
•  6. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.mp4  78.27 MB
•  2. Review of Fundamental Reinforcement Learning Concepts/2. The Explore-Exploit Dilemma.mp4  71.63 MB
•  3. A2C (Advantage Actor-Critic)/7. Multiple Processes.mp4  70.09 MB
•  5. ES (Evolution Strategies)/8. ES for MuJoCo in Code.mp4  68.63 MB
•  4. DDPG (Deep Deterministic Policy Gradient)/6. DDPG Code (part 2).mp4  64.82 MB
•  3. A2C (Advantage Actor-Critic)/1. A2C Section Introduction.mp4  61.3 MB
•  5. ES (Evolution Strategies)/6. Flappy Bird.mp4  60.92 MB
•  6. Appendix FAQ/7. How to Code by Yourself (part 2).mp4  56.7 MB
•  5. ES (Evolution Strategies)/5. ES for Supervised Learning.mp4  55.16 MB
•  1. Welcome/2. Outline.mp4  54.25 MB
•  5. ES (Evolution Strategies)/3. Notes on Evolution Strategies.mp4  53.1 MB
•  2. Review of Fundamental Reinforcement Learning Concepts/6. OpenAI Gym Warmup.mp4  49.72 MB
•  5. ES (Evolution Strategies)/4. ES for Optimizing a Function.mp4  46.51 MB
•  3. A2C (Advantage Actor-Critic)/9. Convolutional Neural Network.mp4  45.66 MB
•  4. DDPG (Deep Deterministic Policy Gradient)/2. Deep Q-Learning (DQN) Review.mp4  45.16 MB
•  5. ES (Evolution Strategies)/1. ES Section Introduction.mp4  44.86 MB
•  6. Appendix FAQ/5. How to Succeed in this Course (Long Version).mp4  39.26 MB
•  3. A2C (Advantage Actor-Critic)/11. A2C Section Summary.mp4  32.72 MB
•  3. A2C (Advantage Actor-Critic)/3. A2C Theory (part 2).mp4  32.59 MB
•  2. Review of Fundamental Reinforcement Learning Concepts/4. Monte Carlo Methods.mp4  32.07 MB
•  2. Review of Fundamental Reinforcement Learning Concepts/7. Review Section Summary.mp4  31.17 MB
•  1. Welcome/1. Introduction.mp4  29.55 MB
•  5. ES (Evolution Strategies)/9. ES Section Summary.mp4  28.64 MB
•  3. A2C (Advantage Actor-Critic)/6. A2C Code - Rough Sketch.mp4  28.49 MB
•  3. A2C (Advantage Actor-Critic)/5. A2C Demo.mp4  27.42 MB
•  1. Welcome/3. Where to get the code.mp4  24.45 MB
•  4. DDPG (Deep Deterministic Policy Gradient)/1. DDPG Section Introduction.mp4  23.92 MB
•  6. Appendix FAQ/9. Python 2 vs Python 3.mp4  18.98 MB
•  2. Review of Fundamental Reinforcement Learning Concepts/1. Review Section Introduction.mp4  18.88 MB
•  6. Appendix FAQ/1. What is the Appendix.mp4  18.07 MB
•  4. DDPG (Deep Deterministic Policy Gradient)/7. DDPG Section Summary.mp4  17.6 MB
•  3. A2C (Advantage Actor-Critic)/4. A2C Theory (part 3).mp4  14.22 MB
•  6. Appendix FAQ/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt  27.68 KB
•  3. A2C (Advantage Actor-Critic)/2. A2C Theory (part 1).vtt  22.8 KB