artificial-intelligence--1iMy7
- 02 Return of the Multi-Armed Bandit\\/007 Updating a Sample Mean.mp42.17MB
- 04 rkov Decision Proccesses\\/031 MDP Summary.mp42.41MB
- 07 Temporal Difference Learning\\/051 Temporal Difference Intro.mp42.72MB
- 02 Return of the Multi-Armed Bandit\\/006 Epsilon-Greedy.mp42.78MB
- 08 Approxition Methods\\/062 Monte Carlo Prediction with Approximation.mp42.84MB
- 05 Dynamic Programming\\/036 Policy Iteration.mp43.13MB
- 04 rkov Decision Proccesses\\/025 Gridworld.mp43.36MB
- 07 Temporal Difference Learning\\/058 TD Sumry.mp43.94MB
- 09 Appendix\\/069 Where to get discount coupons and FREE deep learning terial.mp44.02MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/016 Notes on Assigning Rewards.mp44.22MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/019 Tic Tac Toe Code Representing States.mp44.42MB
- 01 Introduction and Outline\\/003 Where to get the Code.mp44.45MB
- 05 Dynamic Programming\\/035 Policy Improvement.mp44.53MB
- 06 Monte Carlo\\/048 Monte Carlo Control without Exploring Starts.mp44.62MB
- 08 Approxition Methods\\/065 Semi-Gradient SARSA.mp44.70MB
- 05 Dynamic Programming\\/032 Intro to Dynamic Programming and Iterative Policy Evaluation.mp44.83MB
- 07 Temporal Difference Learning\\/056 Q Learning.mp44.84MB
- 05 Dynamic Programming\\/040 Value Iteration in Code.mp44.89MB
- 06 Monte Carlo\\/042 Monte Carlo Intro.mp44.97MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/018 Tic Tac Toe Code Outline.mp45.03MB
- 02 Return of the Multi-Armed Bandit\\/009 Optimistic Initial Values.mp45.12MB
- 04 rkov Decision Proccesses\\/028 Future Rewards.mp45.17MB
- 07 Temporal Difference Learning\\/053 TD0 Prediction in Code.mp45.32MB
- 07 Temporal Difference Learning\\/057 Q Learning in Code.mp45.42MB
- 06 Monte Carlo\\/050 Monte Carlo Sumry.mp45.71MB
- 07 Temporal Difference Learning\\/052 TD0 Prediction.mp45.82MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/014 Naive Solution to Tic-Tac-Toe.mp46.11MB
- 05 Dynamic Programming\\/039 Value Iteration.mp46.18MB
- 08 Approxition Methods\\/061 Features.mp46.24MB
- 04 rkov Decision Proccesses\\/030 Optimal Policy and Optimal Value Function.mp46.31MB
- 08 Approxition Methods\\/059 Approximation Intro.mp46.46MB
- 08 Approxition Methods\\/060 Linear Models for Reinforcement Learning.mp46.46MB
- 02 Return of the Multi-Armed Bandit\\/005 Problem Setup and The Explore-Exploit Dilem.mp46.47MB
- 08 Approxition Methods\\/063 Monte Carlo Prediction with Approximation in Code.mp46.56MB
- 04 rkov Decision Proccesses\\/027 Defining and Formalizing the MDP.mp46.64MB
- 04 rkov Decision Proccesses\\/029 Value Functions.mp47.08MB
- 04 rkov Decision Proccesses\\/026 The Markov Property.mp47.18MB
- 02 Return of the Multi-Armed Bandit\\/013 Nonstationary Bandits.mp47.48MB
- 05 Dynamic Programming\\/037 Policy Iteration in Code.mp47.62MB
- 06 Monte Carlo\\/045 Policy Evaluation in Windy Gridworld.mp47.81MB
- 06 Monte Carlo\\/044 Monte Carlo Policy Evaluation in Code.mp47.91MB
- 02 Return of the Multi-Armed Bandit\\/008 Comparing Different Epsilons.mp48.01MB
- 06 Monte Carlo\\/049 Monte Carlo Control without Exploring Starts in Code.mp48.05MB
- 07 Temporal Difference Learning\\/054 SARSA.mp48.20MB
- 02 Return of the Multi-Armed Bandit\\/010 UCB1.mp48.23MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/024 Tic Tac Toe Sumry.mp48.31MB
- 05 Dynamic Programming\\/041 Dynamic Programming Sumry.mp48.31MB
- 08 Approxition Methods\\/0 TD0 Semi-Gradient Prediction.mp48.35MB
- 06 Monte Carlo\\/043 Monte Carlo Policy Evaluation.mp48.75MB
- 07 Temporal Difference Learning\\/055 SARSA in Code.mp48.82MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/022 Tic Tac Toe Code The Agent.mp49.01MB
- 05 Dynamic Programming\\/038 Policy Iteration in Windy Gridworld.mp49.10MB
- 06 Monte Carlo\\/046 Monte Carlo Control.mp49.26MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/023 Tic Tac Toe Code in Loop and Demo.mp49.44MB
- 01 Introduction and Outline\\/004 Strategy for Passing the Course.mp49.47MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/020 Tic Tac Toe Code Enumerating States Recursively.mp49.79MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/021 Tic Tac Toe Code The Environment.mp410.05MB
- 01 Introduction and Outline\\/001 Introduction and outline.mp410.10MB
- 06 Monte Carlo\\/047 Monte Carlo Control in Code.mp410.17MB
- 02 Return of the Multi-Armed Bandit\\/012 Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp410.57MB
- 08 Approxition Methods\\/066 Semi-Gradient SARSA in Code.mp410.61MB
- 05 Dynamic Programming\\/033 Gridworld in Code.mp411.46MB
- 05 Dynamic Programming\\/034 Iterative Policy Evaluation in Code.mp412.06MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/015 Components of a Reinforcement Learning System.mp412.71MB
- 08 Approxition Methods\\/067 Course Summary and Next Steps.mp413.24MB
- 02 Return of the Multi-Armed Bandit\\/011 Bayesian Thompson Sampling.mp415.23MB
- 01 Introduction and Outline\\/002 What is Reinforcement Learning.mp421.94MB
- 03 Build an Intelligent Tic-Tac-Toe Agent\\/017 The Value Function and Your First Reinforcement Learning Algorithm.mp426.13MB
- 09 Appendix\\/068 How to install Numpy Scipy tplotlib Pandas IPython Theano and TensorFlow.mp443.92MB
- CreateTime2022-06-01
- UpdateTime2022-06-06
- FileTotalCount69
- TotalSize1.08GBHotTimes5ViewTimes10DMCA Report EmailmagnetLinkThunderTorrent DownBaiduYunLatest Search: 1.ANHD-015 2.ADS-004 3.SW-041 4.SDMT-901 5.SAD-188 6.HITMA-24 7.RCT-351 8.SDDE-245 9.HITMA-58 10.ISSD-059 11.FUT-007 12.MIBD-632 13.JFB-006 14.MIBD-461 15.SUPD-104 16.VENU-211 17.KWBD-064 18.MDED-356 19.SWF-147 20.QQ-034 21.ARM-048 22.DJNO-25 23.TGAV-048 24.IDBD-327 25.SQTE-037 26.PSSD-174 27.ONSD-383 28.MIBD-652 29.TSH-001 30.ALD-476 31.IDBD-345 32.RKI-201 33.AAJB-019 34.MIBD-652 35.RKI-151 36.MIBD-527 37.MKCK-055 38.DVH-500 39.HIMA-15 40.TCD-087 41.MNG-92 42.SUGA-01 43.MIBD-728 44.VNDS-2803 45.ONSD-561 46.MOBSND-023 47.BRA-004 48.DOKS-287 49.ETC-057 50.DMBA-085 51.VTF-021 52.VNDS-2676 53.ZFSL-003 54.FE-636 55.SDMS-503 56.OPSD-013 57.IBW-035 58.HUNT-490 59.KMDS-20150 60.RGDR-137 61.DAPJ-052 62.MTVI-007 63.ARMG-037 64.DKLG-002 65.RD-251 66.HMSD-004 67.VIC-013 68.SPRD-397 69.HE-052 70.ALX-421 71.00439 72.245 73.005 74.012 75.008 76.096 77.373 78.117 79.478 80.040 81.005 82.080 83.046 84.015 85.014 86.030 87.297 88.113 89.219 90.851 91.098 92.028 93.002 94.004 95.575 96.149 97.002 98.456 99.630 100.634 101.184 102.235 103.458 104.087 105.038 106.024 107.022 108.162 109.062 110.348 111.20510 112.076 113.225 114.068 115.082 116.178 117.232 118.123 119.044 120.116 121.2045 122.002 123.158 124.010 125.002 126.003 127.102 128.416 129.001 130.056 131.030 132.226 133.951 134.140 135.007 136.101 137.024 138.053 139.2475 140.1060