Taking Machine Learning Models into Production

The chapter discusses the responsibility of taking machine learning models into production, including the role of MLOps engineers and DevOps engineers. It explores the challenges and best practices for deploying models, handling model performance issues, and responding to urgent situations when models break. The speakers also touch upon the impact of large language models and the paradigm shift in managing models as a gateway API.

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