DesireCourse Net Udemy - Advanced AI Deep Reinforcement Learning in Python

1. 1. Introduction and Logistics/1. Introduction and Outline.mp415.84MB
2. 1. Introduction and Logistics/2. Where to get the Code.mp45.19MB
3. 1. Introduction and Logistics/3. How to Succeed in this Course.mp43.3MB
4. 1. Introduction and Logistics/4. Tensorflow or Theano - Your Choice!.mp418.93MB
5. 2. Background Review/1. Review Intro.mp44.2MB
6. 2. Background Review/2. Review of Markov Decision Processes.mp412.3MB
7. 2. Background Review/3. Review of Dynamic Programming.mp46.52MB
8. 2. Background Review/4. Review of Monte Carlo Methods.mp46.18MB
9. 2. Background Review/5. Review of Temporal Difference Learning.mp418.52MB
10. 2. Background Review/6. Review of Approximation Methods for Reinforcement Learning.mp43.67MB
11. 2. Background Review/7. Review of Deep Learning.mp411.05MB
12. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/1. OpenAI Gym Tutorial.mp48.67MB
13. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/10. Theano Warmup.mp45.83MB
14. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/11. Tensorflow Warmup.mp45.06MB
15. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/12. Plugging in a Neural Network.mp45.92MB
16. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/13. OpenAI Gym Section Summary.mp45.32MB
17. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/2. Random Search.mp410.29MB
18. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/3. Saving a Video.mp44.55MB
19. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/4. CartPole with Bins (Theory).mp46.02MB
20. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/5. CartPole with Bins (Code).mp414.7MB
21. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/6. RBF Neural Networks.mp416.51MB
22. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/7. RBF Networks with Mountain Car (Code).mp413.76MB
23. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/8. RBF Networks with CartPole (Theory).mp43.06MB
24. 3. OpenAI Gym and Basic Reinforcement Learning Techniques/9. RBF Networks with CartPole (Code).mp48.92MB
25. 4. TD Lambda/1. N-Step Methods.mp45.03MB
26. 4. TD Lambda/2. N-Step in Code.mp49.47MB
27. 4. TD Lambda/3. TD Lambda.mp411.77MB
28. 4. TD Lambda/4. TD Lambda in Code.mp47.63MB
29. 4. TD Lambda/5. TD Lambda Summary.mp43.65MB
30. 5. Policy Gradients/1. Policy Gradient Methods.mp417.94MB
31. 5. Policy Gradients/10. Policy Gradient Section Summary.mp43.33MB
32. 5. Policy Gradients/2. Policy Gradient in TensorFlow for CartPole.mp417.97MB
33. 5. Policy Gradients/3. Policy Gradient in Theano for CartPole.mp413.44MB
34. 5. Policy Gradients/4. Continuous Action Spaces.mp46.59MB
35. 5. Policy Gradients/5. Mountain Car Continuous Specifics.mp46.51MB
36. 5. Policy Gradients/6. Mountain Car Continuous Theano.mp419.06MB
37. 5. Policy Gradients/7. Mountain Car Continuous Tensorflow.mp420.09MB
38. 5. Policy Gradients/8. Mountain Car Continuous Tensorflow (v2).mp418.78MB
39. 5. Policy Gradients/9. Mountain Car Continuous Theano (v2).mp422.19MB
40. 6. Deep Q-Learning/1. Deep Q-Learning Intro.mp45.9MB
41. 6. Deep Q-Learning/10. Deep Q-Learning Section Summary.mp410.4MB
42. 6. Deep Q-Learning/2. Deep Q-Learning Techniques.mp414.44MB
43. 6. Deep Q-Learning/3. Deep Q-Learning in Tensorflow for CartPole.mp414.98MB
44. 6. Deep Q-Learning/4. Deep Q-Learning in Theano for CartPole.mp413.76MB
45. 6. Deep Q-Learning/5. Additional Implementation Details for Atari.mp48.51MB
46. 6. Deep Q-Learning/6. Pseudocode and Replay Memory.mp427.81MB
47. 6. Deep Q-Learning/7. Deep Q-Learning in Tensorflow for Breakout.mp4234.6MB
48. 6. Deep Q-Learning/8. Deep Q-Learning in Theano for Breakout.mp4233.69MB
49. 6. Deep Q-Learning/9. Partially Observable MDPs.mp47.61MB
50. 7. A3C/1. A3C - Theory and Outline.mp471.76MB
51. 7. A3C/2. A3C - Code pt 1 (Warmup).mp450.09MB
52. 7. A3C/3. A3C - Code pt 2.mp457.61MB
53. 7. A3C/4. A3C - Code pt 3.mp484.52MB
54. 7. A3C/5. A3C - Code pt 4.mp4184.34MB
55. 7. A3C/6. A3C - Section Summary.mp48.85MB
56. 7. A3C/7. Course Summary.mp49.45MB
57. 8. Theano and Tensorflow Basics Review/1. (Review) Theano Basics.mp493.41MB
58. 8. Theano and Tensorflow Basics Review/2. (Review) Theano Neural Network in Code.mp487.01MB
59. 8. Theano and Tensorflow Basics Review/3. (Review) Tensorflow Basics.mp481.42MB
60. 8. Theano and Tensorflow Basics Review/4. (Review) Tensorflow Neural Network in Code.mp497.29MB
61. 9. Appendix FAQ/1. What is the Appendix.mp45.45MB
62. 9. Appendix FAQ/10. Is Theano Dead.mp417.81MB
63. 9. Appendix FAQ/11. What order should I take your courses in (part 1).mp429.32MB
64. 9. Appendix FAQ/12. What order should I take your courses in (part 2).mp437.62MB
65. 9. Appendix FAQ/13. BONUS Where to get Udemy coupons and FREE deep learning material.mp437.84MB
66. 9. Appendix FAQ/2. Windows-Focused Environment Setup 2018.mp4186.16MB
67. 9. Appendix FAQ/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp443.92MB
68. 9. Appendix FAQ/4. How to Code by Yourself (part 1).mp424.53MB
69. 9. Appendix FAQ/5. How to Code by Yourself (part 2).mp414.8MB
70. 9. Appendix FAQ/6. How to Succeed in this Course (Long Version).mp418.31MB
71. 9. Appendix FAQ/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.95MB
72. 9. Appendix FAQ/8. Proof that using Jupyter Notebook is the same as not using it.mp478.24MB
73. 9. Appendix FAQ/9. Python 2 vs Python 3.mp47.83MB