[FreeCourseSite Com] Udemy - Artificial Intelligence Reinforcement Learning In Python

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[FreeCourseSite com] Udemy - Artificial Intelligence Reinforcement Learning in Python

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[FreeCourseSite com] Udemy - Artificial Intelligence Reinforcement Learning in Python.torrent
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23814b5e3b355ce8da598b08b02dc855ceeb3160
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593 MB in 73 files
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Uploaded on 22-02-2018 by our crawler pet called "Spidey".
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Udemy - Artificial Intelligence: Reinforcement Learning in Python

Complete guide to artificial intelligence and machine learning, prep for deep reinforcement learning

For more Udemy Courses: https://freecoursesite.com

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Files in this torrent

FILENAMESIZE
01 Introduction and Outline/001 Introduction and outline.mp410.1 MB
01 Introduction and Outline/002 What is Reinforcement Learning.mp421.9 MB
01 Introduction and Outline/003 Where to get the Code.mp44.4 MB
01 Introduction and Outline/004 Strategy for Passing the Course.mp49.5 MB
02 Return of the Multi-Armed Bandit/005 Problem Setup and The Explore-Exploit Dilemma.mp46.5 MB
02 Return of the Multi-Armed Bandit/006 Epsilon-Greedy.mp42.8 MB
02 Return of the Multi-Armed Bandit/007 Updating a Sample Mean.mp42.2 MB
02 Return of the Multi-Armed Bandit/008 Comparing Different Epsilons.mp48 MB
02 Return of the Multi-Armed Bandit/009 Optimistic Initial Values.mp45.1 MB
02 Return of the Multi-Armed Bandit/010 UCB1.mp48.2 MB
02 Return of the Multi-Armed Bandit/011 Bayesian Thompson Sampling.mp415.2 MB
02 Return of the Multi-Armed Bandit/012 Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp410.6 MB
02 Return of the Multi-Armed Bandit/013 Nonstationary Bandits.mp47.5 MB
03 Build an Intelligent Tic-Tac-Toe Agent/014 Naive Solution to Tic-Tac-Toe.mp46.1 MB
03 Build an Intelligent Tic-Tac-Toe Agent/015 Components of a Reinforcement Learning System.mp412.7 MB
03 Build an Intelligent Tic-Tac-Toe Agent/016 Notes on Assigning Rewards.mp44.2 MB
03 Build an Intelligent Tic-Tac-Toe Agent/017 The Value Function and Your First Reinforcement Learning Algorithm.mp426.1 MB
03 Build an Intelligent Tic-Tac-Toe Agent/018 Tic Tac Toe Code Outline.mp45 MB
03 Build an Intelligent Tic-Tac-Toe Agent/019 Tic Tac Toe Code Representing States.mp44.4 MB
03 Build an Intelligent Tic-Tac-Toe Agent/020 Tic Tac Toe Code Enumerating States Recursively.mp49.8 MB
03 Build an Intelligent Tic-Tac-Toe Agent/021 Tic Tac Toe Code The Environment.mp410 MB
03 Build an Intelligent Tic-Tac-Toe Agent/022 Tic Tac Toe Code The Agent.mp49 MB
03 Build an Intelligent Tic-Tac-Toe Agent/023 Tic Tac Toe Code Main Loop and Demo.mp49.4 MB
03 Build an Intelligent Tic-Tac-Toe Agent/024 Tic Tac Toe Summary.mp48.3 MB
04 Markov Decision Proccesses/025 Gridworld.mp43.4 MB
04 Markov Decision Proccesses/026 The Markov Property.mp47.2 MB
04 Markov Decision Proccesses/027 Defining and Formalizing the MDP.mp46.6 MB
04 Markov Decision Proccesses/028 Future Rewards.mp45.2 MB
04 Markov Decision Proccesses/029 Value Functions.mp47.1 MB
04 Markov Decision Proccesses/030 Optimal Policy and Optimal Value Function.mp46.3 MB
04 Markov Decision Proccesses/031 MDP Summary.mp42.4 MB
05 Dynamic Programming/032 Intro to Dynamic Programming and Iterative Policy Evaluation.mp44.8 MB
05 Dynamic Programming/033 Gridworld in Code.mp411.5 MB
05 Dynamic Programming/034 Iterative Policy Evaluation in Code.mp412.1 MB
05 Dynamic Programming/035 Policy Improvement.mp44.5 MB
05 Dynamic Programming/036 Policy Iteration.mp43.1 MB
05 Dynamic Programming/037 Policy Iteration in Code.mp47.6 MB
05 Dynamic Programming/038 Policy Iteration in Windy Gridworld.mp49.1 MB
05 Dynamic Programming/039 Value Iteration.mp46.2 MB
05 Dynamic Programming/040 Value Iteration in Code.mp44.9 MB
05 Dynamic Programming/041 Dynamic Programming Summary.mp48.3 MB
06 Monte Carlo/042 Monte Carlo Intro.mp45 MB
06 Monte Carlo/043 Monte Carlo Policy Evaluation.mp48.8 MB
06 Monte Carlo/044 Monte Carlo Policy Evaluation in Code.mp47.9 MB
06 Monte Carlo/045 Policy Evaluation in Windy Gridworld.mp47.8 MB
06 Monte Carlo/046 Monte Carlo Control.mp49.3 MB
06 Monte Carlo/047 Monte Carlo Control in Code.mp410.2 MB
06 Monte Carlo/048 Monte Carlo Control without Exploring Starts.mp44.6 MB
06 Monte Carlo/049 Monte Carlo Control without Exploring Starts in Code.mp48 MB
06 Monte Carlo/050 Monte Carlo Summary.mp45.7 MB
07 Temporal Difference Learning/051 Temporal Difference Intro.mp42.7 MB
07 Temporal Difference Learning/052 TD0 Prediction.mp45.8 MB
07 Temporal Difference Learning/053 TD0 Prediction in Code.mp45.3 MB
07 Temporal Difference Learning/054 SARSA.mp48.2 MB
07 Temporal Difference Learning/055 SARSA in Code.mp48.8 MB
07 Temporal Difference Learning/056 Q Learning.mp44.8 MB
07 Temporal Difference Learning/057 Q Learning in Code.mp45.4 MB
07 Temporal Difference Learning/058 TD Summary.mp43.9 MB
08 Approximation Methods/059 Approximation Intro.mp46.5 MB
08 Approximation Methods/060 Linear Models for Reinforcement Learning.mp46.5 MB
08 Approximation Methods/061 Features.mp46.2 MB
08 Approximation Methods/062 Monte Carlo Prediction with Approximation.mp42.8 MB
08 Approximation Methods/063 Monte Carlo Prediction with Approximation in Code.mp46.6 MB
08 Approximation Methods/064 TD0 Semi-Gradient Prediction.mp48.3 MB
08 Approximation Methods/065 Semi-Gradient SARSA.mp44.7 MB
08 Approximation Methods/066 Semi-Gradient SARSA in Code.mp410.6 MB
08 Approximation Methods/067 Course Summary and Next Steps.mp413.2 MB
09 Appendix/068 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp443.9 MB
09 Appendix/069 How to Code by Yourself part 1.mp424.5 MB
09 Appendix/070 How to Code by Yourself part 2.mp414.8 MB
09 Appendix/071 Where to get discount coupons and FREE deep learning material.mp44 MB
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