Intro to Applied Reinforcement Learning

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[masked]pm: Networking & Food[masked]pm: Talk, Demo and Q&A

Presenter: Dialexa --

Deep reinforcement learning is exploding in the AI space thanks to advancements driven by projects like mastering Go, controlling robotic mechanics, and optimizing revenue management. Data-driven organizations are eager to extract the value from this upcoming form of machine learning but can struggle to frame a problem appropriately or build a game plan to execute on. This talk will walk you through the basics of reinforcement learning and how it differs from traditional machine learning, where and how you can apply it in your organization, and a demonstration of an agent learning in action.

The talk will be lead by three senior machine learning engineers at Dialexa. Each has experience designing and implementing reinforcement learning environments and algorithms in previous projects. Rowdy Howell graduated from SMU in 2015 and spearheads the growing data science practice at Dialexa. Jonathan Rebello is a Georgia Tech and University of Texas graduate with five years of experience in preventative maintenance and risk optimization in the oil and gas industry. Finally, Uthman Apatira’s online data science courses have been taken by over 100,000 students internationally.