| 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 |