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Udemy - Artificial Intelligence: Reinforcement Learning in Python


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Torrent File Content (75 files)


[FreeCourseSite.com] Udemy - Artificial Intelligence Reinforcement Learning in Python
    01 Introduction and Outline
          001 Introduction and outline.mp4 -
10.1 MB

          002 What is Reinforcement Learning.mp4 -
21.94 MB

          003 Where to get the Code.mp4 -
4.45 MB

          004 Strategy for Passing the Course.mp4 -
9.47 MB

    02 Return of the Multi-Armed Bandit
          005 Problem Setup and The Explore-Exploit Dilemma.mp4 -
6.47 MB

          006 Epsilon-Greedy.mp4 -
2.78 MB

          007 Updating a Sample Mean.mp4 -
2.17 MB

          008 Comparing Different Epsilons.mp4 -
8.01 MB

          009 Optimistic Initial Values.mp4 -
5.12 MB

          010 UCB1.mp4 -
8.23 MB

          011 Bayesian Thompson Sampling.mp4 -
15.23 MB

          012 Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4 -
10.57 MB

          013 Nonstationary Bandits.mp4 -
7.48 MB

    03 Build an Intelligent Tic-Tac-Toe Agent
          014 Naive Solution to Tic-Tac-Toe.mp4 -
6.11 MB

          015 Components of a Reinforcement Learning System.mp4 -
12.71 MB

          016 Notes on Assigning Rewards.mp4 -
4.22 MB

          017 The Value Function and Your First Reinforcement Learning Algorithm.mp4 -
26.13 MB

          018 Tic Tac Toe Code Outline.mp4 -
5.03 MB

          019 Tic Tac Toe Code Representing States.mp4 -
4.42 MB

          020 Tic Tac Toe Code Enumerating States Recursively.mp4 -
9.79 MB

          021 Tic Tac Toe Code The Environment.mp4 -
10.05 MB

          022 Tic Tac Toe Code The Agent.mp4 -
9.01 MB

          023 Tic Tac Toe Code Main Loop and Demo.mp4 -
9.44 MB

          024 Tic Tac Toe Summary.mp4 -
8.31 MB

    04 Markov Decision Proccesses
          025 Gridworld.mp4 -
3.36 MB

          026 The Markov Property.mp4 -
7.18 MB

          027 Defining and Formalizing the MDP.mp4 -
6.64 MB

          028 Future Rewards.mp4 -
5.17 MB

          029 Value Functions.mp4 -
7.08 MB

          030 Optimal Policy and Optimal Value Function.mp4 -
6.31 MB

          031 MDP Summary.mp4 -
2.41 MB

    05 Dynamic Programming
          032 Intro to Dynamic Programming and Iterative Policy Evaluation.mp4 -
4.83 MB

          033 Gridworld in Code.mp4 -
11.46 MB

          034 Iterative Policy Evaluation in Code.mp4 -
12.06 MB

          035 Policy Improvement.mp4 -
4.53 MB

          036 Policy Iteration.mp4 -
3.13 MB

          037 Policy Iteration in Code.mp4 -
7.62 MB

          038 Policy Iteration in Windy Gridworld.mp4 -
9.1 MB

          039 Value Iteration.mp4 -
6.18 MB

          040 Value Iteration in Code.mp4 -
4.89 MB

          041 Dynamic Programming Summary.mp4 -
8.31 MB

    06 Monte Carlo
          042 Monte Carlo Intro.mp4 -
4.97 MB

          043 Monte Carlo Policy Evaluation.mp4 -
8.75 MB

          044 Monte Carlo Policy Evaluation in Code.mp4 -
7.91 MB

          045 Policy Evaluation in Windy Gridworld.mp4 -
7.81 MB

          046 Monte Carlo Control.mp4 -
9.26 MB

          047 Monte Carlo Control in Code.mp4 -
10.17 MB

          048 Monte Carlo Control without Exploring Starts.mp4 -
4.62 MB

          049 Monte Carlo Control without Exploring Starts in Code.mp4 -
8.05 MB

          050 Monte Carlo Summary.mp4 -
5.71 MB



Description



https://extraimage.net/images/2018/02/22/d861d3e331dca013a8ca53c2a9a6b863.jpg


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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