| 1 - Introduction.mp4 | 3.6 MB | ||
| 10 - Mathematical formulation of reinforcement learning.html | 204.8 B | ||
| 11 - What is value iteration English.srt | 8.5 KB | ||
| 11 - What is value iteration.mp4 | 32.4 MB | ||
| 12 - Value iteration implementation I English.srt | 6.1 KB | ||
| 12 - Value iteration implementation I.mp4 | 34.1 MB | ||
| 13 - Value iteration implementation II English.srt | 5.8 KB | ||
| 13 - Value iteration implementation II.mp4 | 42.8 MB | ||
| 14 - Value iteration implementation III English.srt | 6.7 KB | ||
| 14 - Value iteration implementation III.mp4 | 34.2 MB | ||
| 15 - Value iteration implementation IV English.srt | 9.7 KB | ||
| 15 - Value iteration implementation IV.mp4 | 93.1 MB | ||
| 16 - Value iteration implementation V English.srt | 4.1 KB | ||
| 16 - Value iteration implementation V.mp4 | 19.1 MB | ||
| 17 - What is policy iteration English.srt | 5.3 KB | ||
| 17 - What is policy iteration.mp4 | 9.4 MB | ||
| 18 - Value iteration vs policy iteration English.srt | 3.4 KB | ||
| 18 - Value iteration vs policy iteration.mp4 | 6.7 MB | ||
| 19 - Q learning introduction English.srt | 7.1 KB | ||
| 19 - Q learning introduction.mp4 | 16.1 MB | ||
| 2 - Types of learning.mp4 | 36.2 MB | ||
| 20 - Q learning introduction the algorithm English.srt | 9.6 KB | ||
| 20 - Q learning introduction the algorithm.mp4 | 21.7 MB | ||
| 21 - Q learning illustration English.srt | 15.2 KB | ||
| 21 - Q learning illustration.mp4 | 28.3 MB | ||
| 22 - Mathematical formulation of Q learning.html | 307.2 B | ||
| 23 - PATHFINDING.html | 102.4 B | ||
| 24 - Pathfinding with Qlearning I English.srt | 7 KB | ||
| 24 - Pathfinding with Qlearning I.mp4 | 18.9 MB | ||
| 25 - Pathfinding with Qlearning II English.srt | 6 KB | ||
| 25 - Pathfinding with Qlearning II.mp4 | 25.4 MB | ||
| 26 - Pathfinding with Qlearning III English.srt | 11.7 KB | ||
| 26 - Pathfinding with Qlearning III.mp4 | 109.6 MB | ||
| 27 - Pathfinding with Qlearning IV English.srt | 7.2 KB | ||
| 27 - Pathfinding with Qlearning IV.mp4 | 38.8 MB | ||
| 28 - SHORTEST PATH.html | 307.2 B | ||
| 29 - Shortest path with Qlearning English.srt | 6.5 KB | ||
| 29 - Shortest path with Qlearning.mp4 | 36 MB | ||
| 3 - Applications of reinforcement learning.mp4 | 23.2 MB | ||
| 30 - Exploration vs exploitation problem English.srt | 4.9 KB | ||
| 30 - Exploration vs exploitation problem.mp4 | 10.5 MB | ||
| 31 - Narmed bandit problem introduction English.srt | 11.1 KB | ||
| 31 - Narmed bandit problem introduction.mp4 | 28.1 MB | ||
| 32 - Narmed bandit problem implementation I English.srt | 9.8 KB | ||
| 32 - Narmed bandit problem implementation I.mp4 | 48.2 MB | ||
| 33 - Narmed bandit problem implementation II English.srt | 4.1 KB | ||
| 33 - Narmed bandit problem implementation II.mp4 | 0 B | ||
| 34 - Applications AB testing in marketing English.srt | 5.8 KB | ||
| 34 - Applications AB testing in marketing.mp4 | 0 B | ||
| 35 - What is deep Q learning English.srt | 6.4 KB | ||
| 35 - What is deep Q learning.mp4 | 12.6 MB | ||
| 36 - Deep Q learning and εgreedy strategy English.srt | 4.3 KB | ||
| 37 - Deep Qlearning introduction remember and replay English.srt | 4.8 KB | ||
| 37 - Deep Qlearning introduction remember and replay.mp4 | 9.3 MB | ||
| 38 - Mathematical formulation of deep Q learning.html | 307.2 B | ||
| 39 - Course materials.html | 102.4 B | ||
| 39 - reinforcedlearning.zip | 27.9 KB | ||
| 4 - Markov decision processes basics I.mp4 | 30.5 MB | ||
| 5 - Markov decision processes basics II English.srt | 8.6 KB | ||
| 5 - Markov decision processes basics II.mp4 | 0 B | ||
| 6 - Markov decision processes equations English.srt | 15.1 KB | ||
| 6 - Markov decision processes equations.mp4 | 0 B | ||
| 7 - Markov decision processes illustration English.srt | 9.6 KB | ||
| 7 - Markov decision processes illustration.mp4 | 0 B | ||
| 8 - Bellmanequation English.srt | 7.3 KB | ||
| 8 - Bellmanequation.mp4 | 0 B | ||
| 9 - How to solve MDP problems English.srt | 3.1 KB | ||
| 9 - How to solve MDP problems.mp4 | 8.3 MB | ||
| [Tutorialsplanet.NET].url | 102.4 B | ||
| ▲ 74 total files | |||
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
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 1.8 GB | freecoursewb | 2 weeks | 13 | 11 | |
| 2 GB | freecoursewb | 3 weeks | 27 | 34 | |
| 1.9 GB | freecoursewb | 1 month | 5 | 3 | |
| 2 GB | freecoursewb | 2 months | 15 | 8 | |
| 1.5 GB | freecoursewb | 2 months | 2 | 8 |
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