Explore the latest advancements in MLflow, the widely-used open source platform for managing the full machine learning lifecycle, in this keynote from the Spark + AI Summit 2020. Discover how MLflow simplifies the complex process of standardizing MLOps and productionizing ML models. Learn about new features including simplified experiment tracking, innovations in model format for improved portability, capabilities for managing and comparing model schemas, and enhanced model deployment methods. Gain insights into real-world use cases and understand how MLflow addresses the challenges of reproducibility, agility, and predictability in ML model development and deployment. Delve into topics such as auto-logging, custom tagging, model surfing, and the model registry. Get practical advice on how to leverage these new capabilities to streamline your ML workflows and improve productivity.