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Explore a comprehensive talk on leveraging Docker for self-managed predictive modeling in electric vehicle applications. Discover how to develop and deploy an end-to-end predictive modeling system locally and at scale using Docker as the primary tool. Follow the application lifecycle stages, gaining valuable insights into local development and debugging of Python code with Docker Desktop, Docker Compose, and Kubernetes. Learn about deploying a fleet of continuously updating electric vehicle Digital Twins on Kubernetes. Gain inspiration from the possibilities Docker offers developers and access an open-source project to use as a framework for your own applications. Presented by Alex Iankoulski, Principal Solutions Architect at Amazon Web Services, this 19-minute presentation provides practical knowledge for implementing Docker in predictive modeling workflows.