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[Tutorialsplanet.NET] Udemy - Artificial Intelligence IV - Reinforcement Learning in Java

[Tutorialsplanet.NET] Udemy - Artificial Intelligence IV - Reinforcement Learning in Java

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Description
Udemy - Artificial Intelligence IV - Reinforcement Learning in Java [TP]

All you need to know about Markov Decision processes, value- and policy-iteation as well as about Q learning approach


What you'll learn


Understand reinforcement learning

Understand Markov Decision Processes

Understand value- and policy-iteration

Understand Q-learning approach and it's applications


Requirements


Basics AI knowledge: neural networks in the main

Description


This course is about Reinforcement Learning. The first step is to talk about the mathematical background: we can use a Markov Decision Process as a model for reinforcement learning.

For more Udemy Courses: https://tutorialsplanet.net

File list
  • [Tutorialsplanet.NET] Udemy - Artificial Intelligence IV - Reinforcement Learning in Java
  • 1 - Introduction/1 - Introduction.mp4 3.6 MB
  • 1 - Introduction/2 - Types of learning.mp4 36.2 MB
  • 1 - Introduction/3 - Applications of reinforcement learning.mp4 23.2 MB
  • 2 - Markov Decision Process MDP Theory/10 - Mathematical formulation of reinforcement learning.html 255 B
  • 2 - Markov Decision Process MDP Theory/4 - Markov decision processes basics I.mp4 30.5 MB
  • 2 - Markov Decision Process MDP Theory/5 - Markov decision processes basics II English.srt 8.6 KB
  • 2 - Markov Decision Process MDP Theory/5 - Markov decision processes basics II.mp4 0 B
  • 2 - Markov Decision Process MDP Theory/6 - Markov decision processes equations English.srt 15.1 KB
  • 2 - Markov Decision Process MDP Theory/6 - Markov decision processes equations.mp4 0 B
  • 2 - Markov Decision Process MDP Theory/7 - Markov decision processes illustration English.srt 9.6 KB
  • 2 - Markov Decision Process MDP Theory/7 - Markov decision processes illustration.mp4 0 B
  • 2 - Markov Decision Process MDP Theory/8 - Bellmanequation English.srt 7.3 KB
  • 2 - Markov Decision Process MDP Theory/8 - Bellmanequation.mp4 0 B
  • 2 - Markov Decision Process MDP Theory/9 - How to solve MDP problems English.srt 3.1 KB
  • 2 - Markov Decision Process MDP Theory/9 - How to solve MDP problems.mp4 8.3 MB
  • 3 - Markov Decision Process Value Iteration/11 - What is value iteration English.srt 8.5 KB
  • 3 - Markov Decision Process Value Iteration/11 - What is value iteration.mp4 32.4 MB
  • 3 - Markov Decision Process Value Iteration/12 - Value iteration implementation I English.srt 6.1 KB
  • 3 - Markov Decision Process Value Iteration/12 - Value iteration implementation I.mp4 34.1 MB
  • 3 - Markov Decision Process Value Iteration/13 - Value iteration implementation II English.srt 5.8 KB
  • 3 - Markov Decision Process Value Iteration/13 - Value iteration implementation II.mp4 42.8 MB
  • 3 - Markov Decision Process Value Iteration/14 - Value iteration implementation III English.srt 6.7 KB
  • 3 - Markov Decision Process Value Iteration/14 - Value iteration implementation III.mp4 34.2 MB
  • 3 - Markov Decision Process Value Iteration/15 - Value iteration implementation IV English.srt 9.7 KB
  • 3 - Markov Decision Process Value Iteration/15 - Value iteration implementation IV.mp4 93.1 MB
  • 3 - Markov Decision Process Value Iteration/16 - Value iteration implementation V English.srt 4.1 KB
  • 3 - Markov Decision Process Value Iteration/16 - Value iteration implementation V.mp4 19.1 MB
  • 4 - Markov Decision Process Policy Iteration/17 - What is policy iteration English.srt 5.3 KB
  • 4 - Markov Decision Process Policy Iteration/17 - What is policy iteration.mp4 9.4 MB
  • 4 - Markov Decision Process Policy Iteration/18 - Value iteration vs policy iteration English.srt 3.4 KB
  • 4 - Markov Decision Process Policy Iteration/18 - Value iteration vs policy iteration.mp4 6.7 MB
  • 5 - Q Learning Theory/19 - Q learning introduction English.srt 7.1 KB
  • 5 - Q Learning Theory/19 - Q learning introduction.mp4 16.1 MB
  • 5 - Q Learning Theory/20 - Q learning introduction the algorithm English.srt 9.6 KB
  • 5 - Q Learning Theory/20 - Q learning introduction the algorithm.mp4 21.7 MB
  • 5 - Q Learning Theory/21 - Q learning illustration English.srt 15.2 KB
  • 5 - Q Learning Theory/21 - Q learning illustration.mp4 28.3 MB
  • 5 - Q Learning Theory/22 - Mathematical formulation of Q learning.html 262 B
  • 6 - Pathfinding with QLearning/23 - PATHFINDING.html 73 B
  • 6 - Pathfinding with QLearning/24 - Pathfinding with Qlearning I English.srt 7 KB
  • 6 - Pathfinding with QLearning/24 - Pathfinding with Qlearning I.mp4 18.9 MB
  • 6 - Pathfinding with QLearning/25 - Pathfinding with Qlearning II English.srt 6 KB
  • 6 - Pathfinding with QLearning/25 - Pathfinding with Qlearning II.mp4 25.4 MB
  • 6 - Pathfinding with QLearning/26 - Pathfinding with Qlearning III English.srt 11.7 KB
  • 6 - Pathfinding with QLearning/26 - Pathfinding with Qlearning III.mp4 109.6 MB
  • 6 - Pathfinding with QLearning/27 - Pathfinding with Qlearning IV English.srt 7.2 KB
  • 6 - Pathfinding with QLearning/27 - Pathfinding with Qlearning IV.mp4 38.8 MB
  • 6 - Pathfinding with QLearning/28 - SHORTEST PATH.html 335 B
  • 6 - Pathfinding with QLearning/29 - Shortest path with Qlearning English.srt 6.5 KB
  • 6 - Pathfinding with QLearning/29 - Shortest path with Qlearning.mp4 36 MB
  • 7 - Exploration vs Exploitation Problem/30 - Exploration vs exploitation problem English.srt 4.9 KB
  • 7 - Exploration vs Exploitation Problem/30 - Exploration vs exploitation problem.mp4 10.5 MB
  • 7 - Exploration vs Exploitation Problem/31 - Narmed bandit problem introduction English.srt 11.1 KB
  • 7 - Exploration vs Exploitation Problem/31 - Narmed bandit problem introduction.mp4 28.1 MB
  • 7 - Exploration vs Exploitation Problem/32 - Narmed bandit problem implementation I English.srt 9.8 KB
  • 7 - Exploration vs Exploitation Problem/32 - Narmed bandit problem implementation I.mp4 48.2 MB
  • 7 - Exploration vs Exploitation Problem/33 - Narmed bandit problem implementation II English.srt 4.1 KB
  • 7 - Exploration vs Exploitation Problem/33 - Narmed bandit problem implementation II.mp4 0 B
  • 7 - Exploration vs Exploitation Problem/34 - Applications AB testing in marketing English.srt 5.8 KB
  • 7 - Exploration vs Exploitation Problem/34 - Applications AB testing in marketing.mp4 0 B
  • 8 - Deep Reinforcement Learning Theory/35 - What is deep Q learning English.srt 6.4 KB
  • 8 - Deep Reinforcement Learning Theory/35 - What is deep Q learning.mp4 12.6 MB
  • 8 - Deep Reinforcement Learning Theory/36 - Deep Q learning and εgreedy strategy English.srt 4.3 KB
  • 8 - Deep Reinforcement Learning Theory/37 - Deep Qlearning introduction remember and replay English.srt 4.8 KB
  • 8 - Deep Reinforcement Learning Theory/37 - Deep Qlearning introduction remember and replay.mp4 9.3 MB
  • 8 - Deep Reinforcement Learning Theory/38 - Mathematical formulation of deep Q learning.html 272 B
  • 9 - Course Materials DOWNLOADS/39 - Course materials.html 71 B
  • 9 - Course Materials DOWNLOADS/39 - reinforcedlearning.zip 27.9 KB

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