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[FreeTutorials.Us] deep-reinforcement-learning-in-python

FreeTutorials

种子大小:522.27 MB

收录时间:2017-08-18

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文件列表:49File

  1. 07 Appendix/044 Environment Setup.mp443.92 MB
  2. 07 Appendix/045 How to Code by Yourself part 1.mp424.53 MB
  3. 05 Policy Gradients/035 Mountain Car Continuous Tensorflow.mp420.09 MB
  4. 06 Deep Q-Learning/042 Deep Q-Learning in Theano for Breakout.mp420.03 MB
  5. 05 Policy Gradients/034 Mountain Car Continuous Theano.mp419.06 MB
  6. 05 Policy Gradients/030 Policy Gradient in TensorFlow for CartPole.mp417.97 MB
  7. 05 Policy Gradients/029 Policy Gradient Methods.mp417.94 MB
  8. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/016 RBF Neural Networks.mp416.51 MB
  9. 01 Introduction and Logistics/001 Introduction and Outline.mp415.83 MB
  10. 06 Deep Q-Learning/041 Deep Q-Learning in Tensorflow for Breakout.mp415.76 MB
  11. 06 Deep Q-Learning/038 Deep Q-Learning in Tensorflow for CartPole.mp414.98 MB
  12. 07 Appendix/046 How to Code by Yourself part 2.mp414.8 MB
  13. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/015 CartPole with Bins Code.mp414.7 MB
  14. 06 Deep Q-Learning/037 Deep Q-Learning Techniques.mp414.44 MB
  15. 01 Introduction and Logistics/003 How to Succeed in this Course.mp414.37 MB
  16. 06 Deep Q-Learning/039 Deep Q-Learning in Theano for CartPole.mp413.76 MB
  17. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/017 RBF Networks with Mountain Car Code.mp413.75 MB
  18. 05 Policy Gradients/031 Policy Gradient in Theano for CartPole.mp413.44 MB
  19. 02 Background Review/005 Review of Markov Decision Processes.mp412.25 MB
  20. 04 TD Lambda/026 TD Lambda.mp411.77 MB
  21. 02 Background Review/010 Review of Deep Learning.mp411.04 MB
  22. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/012 Random Search.mp410.29 MB
  23. 04 TD Lambda/025 N-Step in Code.mp49.47 MB
  24. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/019 RBF Networks with CartPole Code.mp48.91 MB
  25. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/011 OpenAI Gym Tutorial.mp48.67 MB
  26. 06 Deep Q-Learning/040 Additional Implementation Details for Atari.mp48.51 MB
  27. 04 TD Lambda/027 TD Lambda in Code.mp47.62 MB
  28. 06 Deep Q-Learning/043 Partially Observable MDPs.mp47.6 MB
  29. 02 Background Review/008 Review of Temporal Difference Learning.mp47.15 MB
  30. 05 Policy Gradients/032 Continuous Action Spaces.mp46.58 MB
  31. 02 Background Review/006 Review of Dynamic Programming.mp46.51 MB
  32. 05 Policy Gradients/033 Mountain Car Continuous Specifics.mp46.5 MB
  33. 02 Background Review/007 Review of Monte Carlo Methods.mp46.18 MB
  34. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/014 CartPole with Bins Theory.mp46.02 MB
  35. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/022 Plugging in a Neural Network.mp45.91 MB
  36. 06 Deep Q-Learning/036 Deep Q-Learning Intro.mp45.9 MB
  37. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/020 Theano Warmup.mp45.83 MB
  38. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/023 OpenAI Gym Section Summary.mp45.31 MB
  39. 01 Introduction and Logistics/002 Where to get the Code.mp45.19 MB
  40. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/021 Tensorflow Warmup.mp45.06 MB
  41. 04 TD Lambda/024 N-Step Methods.mp45.02 MB
  42. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/013 Saving a Video.mp44.54 MB
  43. 02 Background Review/004 Review Intro.mp44.19 MB
  44. 07 Appendix/047 Where to get Udemy coupons and FREE deep learning material.mp44.02 MB
  45. 02 Background Review/009 Review of Approximation Methods for Reinforcement Learning.mp43.67 MB
  46. 04 TD Lambda/028 TD Lambda Summary.mp43.64 MB
  47. 03 OpenAI Gym and Basic Reinforcement Learning Techniques/018 RBF Networks with CartPole Theory.mp43.05 MB
  48. Freetutorials.Us.url119 Bytes
  49. [FreeTutorials.Us].txt75 Bytes