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Reinforcement Learning Explained

Reinforcement Learning (RL) is a machine learning region, where a specialist learns by cooperating with its condition to accomplish an objective.

Self-Paced

Learning Style

Microsoft

Provider

Advanced

Difficulty

42 Hours

Course Duration

Course Info

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Reinforcement Learning (RL) is a machine learning region, where a specialist learns by cooperating with its condition to accomplish an objective.

Course Information

About this course:

Reinforcement Learning (RL) is a machine learning region, where a specialist learns by cooperating with its condition to accomplish an objective.

With this course, we will be acquainted with the universe of reinforcement learning. You will figure out how to outline problems of reinforcement learning and begin handling great models like learning to navigate in a grid-world, news recommendation, and balancing a cart-pole.

You will investigate the essential calculations from dynamic programming, multi-equipped bandits, TD (temporal difference) learning, and progress towards bigger state-space utilizing the approximation of function, specifically utilizing profound learning. Also, you will find out calculations that emphasis on looking through the best strategy with the methods of policy gradient and actor-critic. In this way, you will get acquainted with Project Malmo, a stage for Artificial Intelligence experimentation and research-based over the Minecraft game.

Course Objective:

  • Markov Decision Process
  • Reinforcement Learning Problem
  • Dynamic Programming
  • Approximate Solution Methods
  • Policy Gradient and Actor-Critic
  • Bandits
  • Temporal Difference Learning
  • RL that Works

Audience:

Programmers

Data Analyst

Prerequisite:

No prerequisite required for this course

Outline

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More Information
BrandMicrosoft
SubjectsApp Development
Lab AccessNo
TechnologyMicrosoft
Learning StyleSelf-Paced Learning
Learning TypeCourse
DifficultyAdvanced
Course Duration42 Hours
LanguageEnglish

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