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[FreeTutorials.Us] artificial-intelligence-reinforcement-learning-in-python

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视频 2019-7-11 19:35 2024-12-26 01:30 96 592.52 MB 71
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FreeTutorials Us artificial-intelligence-reinforcement-learning-in-python

文件列表
  1. 01 Introduction and Outline/001 Introduction and outline.mp410.1MB
  2. 01 Introduction and Outline/002 What is Reinforcement Learning.mp421.94MB
  3. 01 Introduction and Outline/003 Where to get the Code.mp44.45MB
  4. 01 Introduction and Outline/004 Strategy for Passing the Course.mp49.47MB
  5. 02 Return of the Multi-Armed Bandit/005 Problem Setup and The Explore-Exploit Dilemma.mp46.47MB
  6. 02 Return of the Multi-Armed Bandit/006 Epsilon-Greedy.mp42.78MB
  7. 02 Return of the Multi-Armed Bandit/007 Updating a Sample Mean.mp42.17MB
  8. 02 Return of the Multi-Armed Bandit/008 Comparing Different Epsilons.mp48.01MB
  9. 02 Return of the Multi-Armed Bandit/009 Optimistic Initial Values.mp45.12MB
  10. 02 Return of the Multi-Armed Bandit/010 UCB1.mp48.23MB
  11. 02 Return of the Multi-Armed Bandit/011 Bayesian Thompson Sampling.mp415.23MB
  12. 02 Return of the Multi-Armed Bandit/012 Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp410.57MB
  13. 02 Return of the Multi-Armed Bandit/013 Nonstationary Bandits.mp47.48MB
  14. 03 Build an Intelligent Tic-Tac-Toe Agent/014 Naive Solution to Tic-Tac-Toe.mp46.11MB
  15. 03 Build an Intelligent Tic-Tac-Toe Agent/015 Components of a Reinforcement Learning System.mp412.71MB
  16. 03 Build an Intelligent Tic-Tac-Toe Agent/016 Notes on Assigning Rewards.mp44.22MB
  17. 03 Build an Intelligent Tic-Tac-Toe Agent/017 The Value Function and Your First Reinforcement Learning Algorithm.mp426.13MB
  18. 03 Build an Intelligent Tic-Tac-Toe Agent/018 Tic Tac Toe Code Outline.mp45.03MB
  19. 03 Build an Intelligent Tic-Tac-Toe Agent/019 Tic Tac Toe Code Representing States.mp44.42MB
  20. 03 Build an Intelligent Tic-Tac-Toe Agent/020 Tic Tac Toe Code Enumerating States Recursively.mp49.79MB
  21. 03 Build an Intelligent Tic-Tac-Toe Agent/021 Tic Tac Toe Code The Environment.mp410.05MB
  22. 03 Build an Intelligent Tic-Tac-Toe Agent/022 Tic Tac Toe Code The Agent.mp49.01MB
  23. 03 Build an Intelligent Tic-Tac-Toe Agent/023 Tic Tac Toe Code Main Loop and Demo.mp49.44MB
  24. 03 Build an Intelligent Tic-Tac-Toe Agent/024 Tic Tac Toe Summary.mp48.31MB
  25. 04 Markov Decision Proccesses/025 Gridworld.mp43.36MB
  26. 04 Markov Decision Proccesses/026 The Markov Property.mp47.18MB
  27. 04 Markov Decision Proccesses/027 Defining and Formalizing the MDP.mp46.64MB
  28. 04 Markov Decision Proccesses/028 Future Rewards.mp45.17MB
  29. 04 Markov Decision Proccesses/029 Value Functions.mp47.08MB
  30. 04 Markov Decision Proccesses/030 Optimal Policy and Optimal Value Function.mp46.31MB
  31. 04 Markov Decision Proccesses/031 MDP Summary.mp42.41MB
  32. 05 Dynamic Programming/032 Intro to Dynamic Programming and Iterative Policy Evaluation.mp44.83MB
  33. 05 Dynamic Programming/033 Gridworld in Code.mp411.46MB
  34. 05 Dynamic Programming/034 Iterative Policy Evaluation in Code.mp412.06MB
  35. 05 Dynamic Programming/035 Policy Improvement.mp44.53MB
  36. 05 Dynamic Programming/036 Policy Iteration.mp43.13MB
  37. 05 Dynamic Programming/037 Policy Iteration in Code.mp47.62MB
  38. 05 Dynamic Programming/038 Policy Iteration in Windy Gridworld.mp49.1MB
  39. 05 Dynamic Programming/039 Value Iteration.mp46.18MB
  40. 05 Dynamic Programming/040 Value Iteration in Code.mp44.89MB
  41. 05 Dynamic Programming/041 Dynamic Programming Summary.mp48.31MB
  42. 06 Monte Carlo/042 Monte Carlo Intro.mp44.97MB
  43. 06 Monte Carlo/043 Monte Carlo Policy Evaluation.mp48.75MB
  44. 06 Monte Carlo/044 Monte Carlo Policy Evaluation in Code.mp47.91MB
  45. 06 Monte Carlo/045 Policy Evaluation in Windy Gridworld.mp47.81MB
  46. 06 Monte Carlo/046 Monte Carlo Control.mp49.26MB
  47. 06 Monte Carlo/047 Monte Carlo Control in Code.mp410.17MB
  48. 06 Monte Carlo/048 Monte Carlo Control without Exploring Starts.mp44.62MB
  49. 06 Monte Carlo/049 Monte Carlo Control without Exploring Starts in Code.mp48.05MB
  50. 06 Monte Carlo/050 Monte Carlo Summary.mp45.71MB
  51. 07 Temporal Difference Learning/051 Temporal Difference Intro.mp42.72MB
  52. 07 Temporal Difference Learning/052 TD0 Prediction.mp45.82MB
  53. 07 Temporal Difference Learning/053 TD0 Prediction in Code.mp45.32MB
  54. 07 Temporal Difference Learning/054 SARSA.mp48.2MB
  55. 07 Temporal Difference Learning/055 SARSA in Code.mp48.82MB
  56. 07 Temporal Difference Learning/056 Q Learning.mp44.84MB
  57. 07 Temporal Difference Learning/057 Q Learning in Code.mp45.42MB
  58. 07 Temporal Difference Learning/058 TD Summary.mp43.94MB
  59. 08 Approximation Methods/059 Approximation Intro.mp46.46MB
  60. 08 Approximation Methods/060 Linear Models for Reinforcement Learning.mp46.46MB
  61. 08 Approximation Methods/061 Features.mp46.24MB
  62. 08 Approximation Methods/062 Monte Carlo Prediction with Approximation.mp42.84MB
  63. 08 Approximation Methods/063 Monte Carlo Prediction with Approximation in Code.mp46.56MB
  64. 08 Approximation Methods/064 TD0 Semi-Gradient Prediction.mp48.35MB
  65. 08 Approximation Methods/065 Semi-Gradient SARSA.mp44.7MB
  66. 08 Approximation Methods/066 Semi-Gradient SARSA in Code.mp410.61MB
  67. 08 Approximation Methods/067 Course Summary and Next Steps.mp413.24MB
  68. 09 Appendix/068 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp443.92MB
  69. 09 Appendix/069 How to Code by Yourself part 1.mp424.53MB
  70. 09 Appendix/070 How to Code by Yourself part 2.mp414.8MB
  71. 09 Appendix/071 Where to get discount coupons and FREE deep learning material.mp44.02MB
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