589689.xyz

GetFreeCourses.Me-Udemy-Cutting-Edge AI Deep Reinforcement Learning in Python

  • 收录时间:2020-02-23 17:30:33
  • 文件大小:3GB
  • 下载次数:94
  • 最近下载:2021-01-08 14:14:38
  • 磁力链接:
立即下载 复制链接

文件列表

  1. 6. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4 194MB
  2. 4. DDPG (Deep Deterministic Policy Gradient)/5. DDPG Code (part 1).mp4 194MB
  3. 3. A2C (Advantage Actor-Critic)/10. A2C.mp4 192MB
  4. 6. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 167MB
  5. 5. ES (Evolution Strategies)/7. ES for Flappy Bird in Code.mp4 142MB
  6. 6. Appendix FAQ/11. What order should I take your courses in (part 2).mp4 139MB
  7. 3. A2C (Advantage Actor-Critic)/8. Environment Wrappers.mp4 129MB
  8. 6. Appendix FAQ/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 118MB
  9. 4. DDPG (Deep Deterministic Policy Gradient)/4. MuJoCo.mp4 110MB
  10. 2. Review of Fundamental Reinforcement Learning Concepts/3. Markov Decision Processes (MDPs).mp4 109MB
  11. 5. ES (Evolution Strategies)/2. ES Theory.mp4 108MB
  12. 6. Appendix FAQ/10. What order should I take your courses in (part 1).mp4 99MB
  13. 3. A2C (Advantage Actor-Critic)/2. A2C Theory (part 1).mp4 96MB
  14. 6. Appendix FAQ/6. How to Code by Yourself (part 1).mp4 83MB
  15. 4. DDPG (Deep Deterministic Policy Gradient)/3. DDPG Theory.mp4 81MB
  16. 2. Review of Fundamental Reinforcement Learning Concepts/5. Temporal Difference Learning (TD).mp4 79MB
  17. 6. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.mp4 78MB
  18. 2. Review of Fundamental Reinforcement Learning Concepts/2. The Explore-Exploit Dilemma.mp4 72MB
  19. 3. A2C (Advantage Actor-Critic)/7. Multiple Processes.mp4 70MB
  20. 5. ES (Evolution Strategies)/8. ES for MuJoCo in Code.mp4 69MB
  21. 4. DDPG (Deep Deterministic Policy Gradient)/6. DDPG Code (part 2).mp4 65MB
  22. 3. A2C (Advantage Actor-Critic)/1. A2C Section Introduction.mp4 61MB
  23. 5. ES (Evolution Strategies)/6. Flappy Bird.mp4 61MB
  24. 6. Appendix FAQ/7. How to Code by Yourself (part 2).mp4 57MB
  25. 5. ES (Evolution Strategies)/5. ES for Supervised Learning.mp4 55MB
  26. 1. Welcome/2. Outline.mp4 54MB
  27. 5. ES (Evolution Strategies)/3. Notes on Evolution Strategies.mp4 53MB
  28. 2. Review of Fundamental Reinforcement Learning Concepts/6. OpenAI Gym Warmup.mp4 50MB
  29. 5. ES (Evolution Strategies)/4. ES for Optimizing a Function.mp4 47MB
  30. 3. A2C (Advantage Actor-Critic)/9. Convolutional Neural Network.mp4 46MB
  31. 4. DDPG (Deep Deterministic Policy Gradient)/2. Deep Q-Learning (DQN) Review.mp4 45MB
  32. 5. ES (Evolution Strategies)/1. ES Section Introduction.mp4 45MB
  33. 6. Appendix FAQ/5. How to Succeed in this Course (Long Version).mp4 39MB
  34. 3. A2C (Advantage Actor-Critic)/11. A2C Section Summary.mp4 33MB
  35. 3. A2C (Advantage Actor-Critic)/3. A2C Theory (part 2).mp4 33MB
  36. 2. Review of Fundamental Reinforcement Learning Concepts/4. Monte Carlo Methods.mp4 32MB
  37. 2. Review of Fundamental Reinforcement Learning Concepts/7. Review Section Summary.mp4 31MB
  38. 1. Welcome/1. Introduction.mp4 30MB
  39. 5. ES (Evolution Strategies)/9. ES Section Summary.mp4 29MB
  40. 3. A2C (Advantage Actor-Critic)/6. A2C Code - Rough Sketch.mp4 28MB
  41. 3. A2C (Advantage Actor-Critic)/5. A2C Demo.mp4 27MB
  42. 1. Welcome/3. Where to get the code.mp4 24MB
  43. 4. DDPG (Deep Deterministic Policy Gradient)/1. DDPG Section Introduction.mp4 24MB
  44. 6. Appendix FAQ/9. Python 2 vs Python 3.mp4 19MB
  45. 2. Review of Fundamental Reinforcement Learning Concepts/1. Review Section Introduction.mp4 19MB
  46. 6. Appendix FAQ/1. What is the Appendix.mp4 18MB
  47. 4. DDPG (Deep Deterministic Policy Gradient)/7. DDPG Section Summary.mp4 18MB
  48. 3. A2C (Advantage Actor-Critic)/4. A2C Theory (part 3).mp4 14MB
  49. 6. Appendix FAQ/4. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 28KB
  50. 3. A2C (Advantage Actor-Critic)/2. A2C Theory (part 1).vtt 23KB
  51. 5. ES (Evolution Strategies)/2. ES Theory.vtt 22KB
  52. 2. Review of Fundamental Reinforcement Learning Concepts/3. Markov Decision Processes (MDPs).vtt 22KB
  53. 4. DDPG (Deep Deterministic Policy Gradient)/4. MuJoCo.vtt 21KB
  54. 6. Appendix FAQ/11. What order should I take your courses in (part 2).vtt 20KB
  55. 4. DDPG (Deep Deterministic Policy Gradient)/3. DDPG Theory.vtt 20KB
  56. 4. DDPG (Deep Deterministic Policy Gradient)/5. DDPG Code (part 1).vtt 20KB
  57. 3. A2C (Advantage Actor-Critic)/10. A2C.vtt 20KB
  58. 6. Appendix FAQ/6. How to Code by Yourself (part 1).vtt 19KB
  59. 2. Review of Fundamental Reinforcement Learning Concepts/5. Temporal Difference Learning (TD).vtt 19KB
  60. 6. Appendix FAQ/2. Windows-Focused Environment Setup 2018.vtt 17KB
  61. 2. Review of Fundamental Reinforcement Learning Concepts/2. The Explore-Exploit Dilemma.vtt 16KB
  62. 5. ES (Evolution Strategies)/7. ES for Flappy Bird in Code.vtt 16KB
  63. 6. Appendix FAQ/10. What order should I take your courses in (part 1).vtt 14KB
  64. 5. ES (Evolution Strategies)/6. Flappy Bird.vtt 14KB
  65. 3. A2C (Advantage Actor-Critic)/8. Environment Wrappers.vtt 13KB
  66. 6. Appendix FAQ/5. How to Succeed in this Course (Long Version).vtt 13KB
  67. 6. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 13KB
  68. 6. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.vtt 12KB
  69. 6. Appendix FAQ/7. How to Code by Yourself (part 2).vtt 11KB
  70. 4. DDPG (Deep Deterministic Policy Gradient)/2. Deep Q-Learning (DQN) Review.vtt 10KB
  71. 5. ES (Evolution Strategies)/3. Notes on Evolution Strategies.vtt 10KB
  72. 3. A2C (Advantage Actor-Critic)/7. Multiple Processes.vtt 10KB
  73. 1. Welcome/2. Outline.vtt 9KB
  74. 3. A2C (Advantage Actor-Critic)/1. A2C Section Introduction.vtt 9KB
  75. 2. Review of Fundamental Reinforcement Learning Concepts/4. Monte Carlo Methods.vtt 8KB
  76. 2. Review of Fundamental Reinforcement Learning Concepts/7. Review Section Summary.vtt 8KB
  77. 3. A2C (Advantage Actor-Critic)/6. A2C Code - Rough Sketch.vtt 8KB
  78. 5. ES (Evolution Strategies)/8. ES for MuJoCo in Code.vtt 8KB
  79. 3. A2C (Advantage Actor-Critic)/3. A2C Theory (part 2).vtt 8KB
  80. 3. A2C (Advantage Actor-Critic)/11. A2C Section Summary.vtt 8KB
  81. 5. ES (Evolution Strategies)/1. ES Section Introduction.vtt 8KB
  82. 2. Review of Fundamental Reinforcement Learning Concepts/6. OpenAI Gym Warmup.vtt 7KB
  83. 5. ES (Evolution Strategies)/4. ES for Optimizing a Function.vtt 7KB
  84. 5. ES (Evolution Strategies)/5. ES for Supervised Learning.vtt 7KB
  85. 4. DDPG (Deep Deterministic Policy Gradient)/6. DDPG Code (part 2).vtt 6KB
  86. 3. A2C (Advantage Actor-Critic)/9. Convolutional Neural Network.vtt 6KB
  87. 5. ES (Evolution Strategies)/9. ES Section Summary.vtt 6KB
  88. 1. Welcome/3. Where to get the code.vtt 6KB
  89. 6. Appendix FAQ/9. Python 2 vs Python 3.vtt 5KB
  90. 4. DDPG (Deep Deterministic Policy Gradient)/7. DDPG Section Summary.vtt 5KB
  91. 2. Review of Fundamental Reinforcement Learning Concepts/1. Review Section Introduction.vtt 5KB
  92. 1. Welcome/1. Introduction.vtt 4KB
  93. 4. DDPG (Deep Deterministic Policy Gradient)/1. DDPG Section Introduction.vtt 4KB
  94. 3. A2C (Advantage Actor-Critic)/4. A2C Theory (part 3).vtt 3KB
  95. 6. Appendix FAQ/1. What is the Appendix.vtt 3KB
  96. 3. A2C (Advantage Actor-Critic)/5. A2C Demo.vtt 2KB
  97. How you can help GetFreeCourses.Me.txt 182B
  98. GetFreeCourses.Me.url 116B