Dean Wampler is an expert in data engineering for scalable streaming data systems and applications of machine learning and artificial intelligence (ML/AI). He is a Principal Software Engineer at Domino Data Lab. Previously he worked at Anyscale and Lightbend, where he worked on scalable ML with Ray and distributed streaming data systems with Apache Spark, Apache Kafka, Kubernetes, and other tools. Dean is the author of several books and reports from O’Reilly. He is a contributor to several open source projects, a frequent conference speaker. He also co-organizes several conferences around the world and several user groups in Chicago. Dean has a Ph.D. in Physics from the University of Washington. Find Dean on Twitter: @deanwampler.
"Reinforcement Learning with Ray and RLlib"
Tuesday, 9/22 @ 11:45am - 12:45pm
Reinforcement learning trains an agent to maximize a reward in an environment. We’ll start with why RL is important, how it works, several applications of RL and the compute challenges RL creates.
Then we’ll see how RLlib, implemented with Ray, seamlessly and efficiently supports RL, providing an ideal platform for building Python-based, RL applications with an intuitive, flexible API.