14–17 Oct 2019
Emily Webber

Emily Webber
Machine Learning Specialist Solutions Architect, Amazon Web Services

Emily Webber is a machine learning specialist solutions architect at Amazon Web Services (AWS). She guides customers from project ideation to full deployment, focusing on Amazon SageMaker, where her customers are household names across the world, such as T-Mobile. She’s been leading data science projects for many years, piloting the application of machine learning into such diverse areas as social media violence detection, economic policy evaluation, computer vision, reinforcement learning, the IoT, drones, and robotic design. Previously, she was a data scientist at the Federal Reserve Bank of Chicago and a solutions architect for an explainable AI startup in Chicago. Her master’s degree is from the University of Chicago, where she developed new applications of machine learning for public policy research with the Data Science for Social Good Fellowship.

Sessions

9:409:55 Wednesday, 16 October 2019
Location: King's Suite
Secondary topics:  Reinforcement Learning
Emily Webber (Amazon Web Services)
Average rating: ****.
(4.40, 15 ratings)
If you've ever wondered if you could use AI to inform public policy, join Emily Webber as she combines classic economic methods with AI techniques to train a reinforcement learning agent on decades of randomized control trials. You'll learn about classic philosophical foundations for public policy decision making and how these can be applied to solve the problems that impact the many. Read more.

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