[FreeCourseSite.com] Udemy - Advanced AI Deep Reinforcement Learning in Python

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[FreeCourseSite.com] Udemy - Advanced AI Deep Reinforcement Learning in Python.torrent

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种子哈希:29D08CB6318B69258792FFA3B774C24DD31F86D4
文件大小:2.96GB
创建时间:2021-01-14
下载热度:58154
下载速度:极快
最近访问:2021-01-14

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种子包含的文件

[FreeCourseSite.com] Udemy - Advanced AI Deep Reinforcement Learning in Python.torrent

1. 6. Deep Q-Learning/7. Deep Q-Learning in Tensorflow for Breakout.mp4 234.61MB

2. 6. Deep Q-Learning/8. Deep Q-Learning in Theano for Breakout.mp4 233.69MB

3. 9. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 186.16MB

4. 7. A3C/5. A3C - Code pt 4.mp4 184.35MB

5. 2. The Basics of Reinforcement Learning/2. Elements of a Reinforcement Learning Problem.mp4 105.25MB

6. 8. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp4 97.30MB

7. 8. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp4 93.40MB

8. 8. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp4 87.00MB

9. 7. A3C/4. A3C - Code pt 3.mp4 84.52MB

10. 8. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp4 81.43MB

11. 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4 78.25MB

12. 1. Introduction and Logistics/3. Anyone Can Succeed in this Course.mp4 77.87MB

13. 7. A3C/1. A3C - Theory and Outline.mp4 71.77MB

14. 2. The Basics of Reinforcement Learning/11. Q-Learning.mp4 67.09MB

15. 7. A3C/3. A3C - Code pt 2.mp4 57.60MB

16. 2. The Basics of Reinforcement Learning/9. Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4 57.32MB

17. 2. The Basics of Reinforcement Learning/4. Markov Decision Processes (MDPs).mp4 50.87MB

18. 1. Introduction and Logistics/1. Introduction and Outline.mp4 50.49MB

19. 7. A3C/2. A3C - Code pt 1 (Warmup).mp4 50.10MB

20. 2. The Basics of Reinforcement Learning/6. Value Functions and the Bellman Equation.mp4 48.15MB

21. 2. The Basics of Reinforcement Learning/3. States, Actions, Rewards, Policies.mp4 44.52MB

22. 9. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.92MB

23. 2. The Basics of Reinforcement Learning/8. Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4 42.88MB

24. 2. The Basics of Reinforcement Learning/10. Epsilon-Greedy.mp4 41.83MB

25. 2. The Basics of Reinforcement Learning/1. Reinforcement Learning Section Introduction.mp4 40.98MB

26. 2. The Basics of Reinforcement Learning/12. How to Learn Reinforcement Learning.mp4 40.56MB

27. 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 38.96MB

28. 12. Appendix FAQ Finale/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 37.85MB

29. 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 37.63MB

30. 2. The Basics of Reinforcement Learning/7. What does it mean to “learn”.mp4 32.88MB

31. 1. Introduction and Logistics/2. Where to get the Code.mp4 30.42MB

32. 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 29.33MB

33. 6. Deep Q-Learning/6. Pseudocode and Replay Memory.mp4 27.81MB

34. 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4 24.53MB

35. 2. The Basics of Reinforcement Learning/5. The Return.mp4 23.77MB

36. 5. Policy Gradients/9. Mountain Car Continuous Theano (v2).mp4 22.20MB

37. 5. Policy Gradients/7. Mountain Car Continuous Tensorflow.mp4 20.09MB

38. 5. Policy Gradients/6. Mountain Car Continuous Theano.mp4 19.06MB

39. 1. Introduction and Logistics/4. Tensorflow or Theano - Your Choice!.mp4 18.93MB

40. 5. Policy Gradients/8. Mountain Car Continuous Tensorflow (v2).mp4 18.78MB

41. 11. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).mp4 18.32MB

42. 5. Policy Gradients/2. Policy Gradient in TensorFlow for CartPole.mp4 17.97MB

43. 5. Policy Gradients/1. Policy Gradient Methods.mp4 17.94MB

44. 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/5. Is Theano Dead.mp4 17.82MB

45. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/6. RBF Neural Networks.mp4 16.51MB

46. 2. The Basics of Reinforcement Learning/13. Suggestion Box.mp4 16.13MB

47. 4. TD Lambda/1. N-Step Methods.mp4 15.56MB

48. 6. Deep Q-Learning/3. Deep Q-Learning in Tensorflow for CartPole.mp4 14.98MB

49. 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).mp4 14.81MB

50. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/5. CartPole with Bins (Code).mp4 14.71MB

51. 6. Deep Q-Learning/2. Deep Q-Learning Techniques.mp4 14.45MB

52. 6. Deep Q-Learning/4. Deep Q-Learning in Theano for CartPole.mp4 13.77MB

53. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/7. RBF Networks with Mountain Car (Code).mp4 13.75MB

54. 5. Policy Gradients/3. Policy Gradient in Theano for CartPole.mp4 13.45MB

55. 4. TD Lambda/3. TD Lambda.mp4 11.78MB

56. 6. Deep Q-Learning/10. Deep Q-Learning Section Summary.mp4 10.41MB

57. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/2. Random Search.mp4 10.29MB

58. 4. TD Lambda/2. N-Step in Code.mp4 9.48MB

59. 7. A3C/7. Course Summary.mp4 9.45MB

60. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/9. RBF Networks with CartPole (Code).mp4 8.91MB

61. 7. A3C/6. A3C - Section Summary.mp4 8.85MB

62. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/1. OpenAI Gym Tutorial.mp4 8.67MB

63. 6. Deep Q-Learning/5. Additional Implementation Details for Atari.mp4 8.51MB

64. 10. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.mp4 7.84MB

65. 4. TD Lambda/4. TD Lambda in Code.mp4 7.63MB

66. 6. Deep Q-Learning/9. Partially Observable MDPs.mp4 7.61MB

67. 5. Policy Gradients/4. Continuous Action Spaces.mp4 6.59MB

68. 5. Policy Gradients/5. Mountain Car Continuous Specifics.mp4 6.50MB

69. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/4. CartPole with Bins (Theory).mp4 6.03MB

70. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/12. Plugging in a Neural Network.mp4 5.91MB

71. 6. Deep Q-Learning/1. Deep Q-Learning Intro.mp4 5.91MB

72. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/10. Theano Warmup.mp4 5.83MB

73. 12. Appendix FAQ Finale/1. What is the Appendix.mp4 5.45MB

74. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/13. OpenAI Gym Section Summary.mp4 5.31MB

75. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/11. Tensorflow Warmup.mp4 5.06MB

76. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/3. Saving a Video.mp4 4.54MB

77. 4. TD Lambda/5. TD Lambda Summary.mp4 3.65MB

78. 5. Policy Gradients/10. Policy Gradient Section Summary.mp4 3.32MB

79. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/8. RBF Networks with CartPole (Theory).mp4 3.06MB

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