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Reinforcement Machine Learning

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Track :

Programming

Lessons no : 9

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What will you learn in this course?
  • Develop strategies for designing reinforcement learning algorithms for complex decision-making tasks in real-world environments
  • Implement reward shaping techniques to optimize agent performance in reinforcement learning applications
  • Analyze and interpret environment feedback to improve reinforcement learning agent behaviors and outcomes
  • Apply value-based and policy-based methods to train reinforcement learning agents across diverse domains
  • Evaluate the effectiveness of different exploration-exploitation strategies in reinforcement learning scenarios
  • Integrate reinforcement learning models with existing machine learning systems for enhanced autonomous decision-making

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Lessons | 9


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4.7
12 Reviews
Evren Efe BALCI 

.
2025-12-18

Kaviya B 

Nice
2025-11-25

KANISHA S CSE 

Good
2025-11-25

ISWARYA P CSE 

Informative
2025-11-25

Mirthun K S 

Nice
2025-10-31

NANTHA KISHORE S CSE 

It was good
2025-10-28

Muralidharan P D 

.
2025-10-18

KEERTHIVASAN PUGALENTHI CSE 

Good
2025-10-15

Jagatheshkumar MG 

-
2025-10-14

KEERTAN KUMAR S CSE 

noice
2025-10-13

Nuraidar Mambetaly 

Amazing
2025-09-10

DINESHKUMAR V 

Good
2025-07-27

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Reinforcement learning is a machine learning training method based on rewarding desired behaviors and/or punishing undesired ones. In general, a reinforcement learning agent is able to perceive and interpret its environment .