Lynda - Reinforcement Learning Foundations

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Reinforcement Learning Foundations [TutsNode.com] - Reinforcement Learning Foundations
  • 01 Reinforcement learning in a nutshell.mp4 (20.9 MB)
  • 04 Markov decision process.en.srt (7.0 KB)
  • 16 SARSA.en.srt (6.8 KB)
  • 03 A basic RL problem.en.srt (6.7 KB)
  • 06 Monte Carlo method.en.srt (4.7 KB)
  • 14 Additional modifications.en.srt (4.2 KB)
  • 02 Terms in reinforcement learning.en.srt (3.7 KB)
  • 05 A basic RL solution.en.srt (3.5 KB)
  • 10 Exploration and exploitation.en.srt (3.5 KB)
  • 01 Reinforcement learning in a nutshell.en.srt (3.5 KB)
  • 17 SARSAMAX (Q-learning).en.srt (3.2 KB)
  • 22 Your reinforcement learning journey.en.srt (2.8 KB)
  • 07 Temporal difference methods.en.srt (1.8 KB)
  • 04 Markov decision process.mp4 (17.4 MB)
  • 12 First visit and every visit MC prediction.en.srt (2.7 KB)
  • 09 The setting.en.srt (2.0 KB)
  • 11 Monte Carlo prediction.en.srt (2.7 KB)
  • 08 Other RL algorithms.en.srt (0.9 KB)
  • 18 Expected SARSA.en.srt (2.5 KB)
  • 19 Deep reinforcement learning.en.srt (2.2 KB)
  • 15 The setting.en.srt (1.8 KB)
  • 21 Inverse reinforcement learning.en.srt (1.8 KB)
  • 20 Multi-agent reinforcement learning.en.srt (1.7 KB)
  • 13 Monte Carlo control.en.srt (1.4 KB)
  • 16 SARSA.mp4 (15.2 MB)
  • 03 A basic RL problem.mp4 (15.1 MB)
  • 06 Monte Carlo method.mp4 (12.2 MB)
  • 14 Additional modifications.mp4 (10.6 MB)
  • 02 Terms in reinforcement learning.mp4 (10.2 MB)
  • 17 SARSAMAX (Q-learning).mp4 (9.1 MB)
  • 05 A basic RL solution.mp4 (8.6 MB)
  • 10 Exploration and exploitation.mp4 (7.7 MB)
  • 18 Expected SARSA.mp4 (7.1 MB)
  • 12 First visit and every visit MC prediction.mp4 (6.8 MB)
  • 22 Your reinforcement learning journey.mp4 (6.2 MB)
  • 15 The setting.mp4 (5.2 MB)
  • 11 Monte Carlo prediction.mp4 (4.6 MB)
  • 19 Deep reinforcement learning.mp4 (4.3 MB)
  • 20 Multi-agent reinforcement learning.mp4 (4.2 MB)
  • 21 Inverse reinforcement learning.mp4 (4.1 MB)
  • 07 Temporal difference methods.mp4 (3.9 MB)
  • 08 Other RL algorithms.mp4 (3.2 MB)
  • 13 Monte Carlo control.mp4 (3.1 MB)
  • 09 The setting.mp4 (2.9 MB)
  • TutsNode.com.txt (0.1 KB)
  • [TGx]Downloaded from torrentgalaxy.to .txt (0.6 KB)
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Description


Description

Innovations in finance, health, robotics, and a variety of other sectors have been made possible with reinforcement learning (RL), which involves the training of machines to learn from their environment. Many top tech companies are investing heavily in this field. In this course, instructor Khaulat Abdulhakeem helps you learn the basics of this relatively new, but valuable skill. Get to know the key terminology used in RL, how RL plays a major role in the advancement of AI, and the kinds of problems you can use RL to solve. Khaulat shows you how to define and represent reinforcement learning problems. She also delves into RL algorithms, including the Monte Carlo and temporal difference methods. Plus, she explores deep and multi-agent RL, as well as how inverse learning works and how it can help agents learn by imitation.

Released 1/22/2021



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Lynda - Reinforcement Learning Foundations

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184.9 MB
seeders:14
leechers:2
Lynda - Reinforcement Learning Foundations

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