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Explore the challenges and solutions of deploying MLOps to scale machine learning at M&S in this insightful conference talk from the Data Science Festival. Delve into the complexities of constructing production-level machine learning systems and learn how MLOps practices can overcome obstacles absent from proof of concepts and small-scale research projects. Discover how M&S implements reproducibility, automated testing, and monitoring in their ML systems delivery, alongside crucial checks like data verification and model quality. Examine two diverse use cases spanning from one-to-one personalization for enhanced customer experiences to enterprise functions that improve business operations. Gain valuable insights into how M&S projects follow the ML maturity rubric and implement key testing and monitoring tools to ensure production-readiness of their ML systems. Learn from speakers Nick Masca, Sam Comber, and Duong Le as they share their experiences in scaling machine learning and deploying MLOps at M&S.
