Reinforcement Learning (RL), and more recently Deep Reinforcement Learning, achieved impressive results in many domains, such as AlphaGo (2016) and AlphaZero (2017). Like a human, Reinforcement Learning agents learn for themselves to achieve successful strategies that lead to the optimal long-term rewards. This error and trial learning strategy is the key differentiator between RL methodologies and the other traditional ML approaches. In this presentation, we propose an introduction to Reinforcement Learning and Deep RL, the main recent achievements and techniques, and the most salient challenges faced by the RL community to scale and deploy these systems in the real world.
Please join
@Sarah Boufelja in this on demand webinar for
Introduction to Reinforcement and Deep Reinforcement Learning: DSE Presents Chat with the Lab webinar.
Share any of your questions below and
register to watch here.
Thanks,
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JORGE CASTANON
Chat with labs webinar series:
https://ibm.co/Chat-With-The-Lab-Webinar------------------------------
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