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Meeting Summary

AIM404-R1 - [REPEAT 1] Amazon SageMaker RL: Solving business problems with RL and bandits

Session Description

In reinforcement learning (RL), an RL agent learns in an interactive environment by trial and error using feedback from its own actions, and can make sophisticated multi-step decisions. As a result, RL has broad applicability in robotics, industrial control, finance, HVAC, dialog systems, online advertising, and more. This workshop provides practitioners with hands-on experience building and deploying RL agents from scratch. We use examples from two scenarios: one where the environment can be simulated (computer games, resource allocation simulators, etc.) and one where it cannot be and the agent learns in a live environment (recommender systems, trading bots, etc.).


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Additional Information
Artificial Intelligence & Machine Learning
400 - Expert
Please note that session information is subject to change.
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