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Machine Learning Mini Series - What is Reinforcement Learning?

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Manage episode 424226538 series 3578824
Content provided by Emily Laird. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Emily Laird or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode of our machine learning mini-series, we explore the world of Reinforcement Learning (RL). Think of RL as the rebellious teenager of the machine learning family, eager to learn through trial and error. We’ll break down the basics: from agents and environments to actions, rewards, and policies. Using engaging analogies like training a dog or a game show contestant, we’ll explore real-world applications, including self-driving cars, video games, robotics, and marketing. Plus, we'll discuss the challenges of balancing exploration with exploitation and the hefty data requirements that make RL both fascinating and formidable.

Connect with Emily Laird on LinkedIn

  continue reading

24 episodes

Artwork
iconShare
 
Manage episode 424226538 series 3578824
Content provided by Emily Laird. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Emily Laird or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode of our machine learning mini-series, we explore the world of Reinforcement Learning (RL). Think of RL as the rebellious teenager of the machine learning family, eager to learn through trial and error. We’ll break down the basics: from agents and environments to actions, rewards, and policies. Using engaging analogies like training a dog or a game show contestant, we’ll explore real-world applications, including self-driving cars, video games, robotics, and marketing. Plus, we'll discuss the challenges of balancing exploration with exploitation and the hefty data requirements that make RL both fascinating and formidable.

Connect with Emily Laird on LinkedIn

  continue reading

24 episodes

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