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Learn how companies safely deploy new machine learning models to production using controlled strategies like A/B testing, canary deployment, and shadow testing.
Learn to build a robust AI project framework that incorporates Gartner's three key strategies for AI success: building capacity, creating partnerships, and avoiding random exploration.
Learn how MLflow streamlines the entire machine learning lifecycle, from experiment tracking to model deployment, enabling scalable and reproducible workflows in production environments.
