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From Scratch to Success: Building an MLOps Team and ML Platform - Simon Stiebellehner

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The Importance of Understanding the Data Science Workflow

A successful ML platform engineer or MLOps engineer, I sometimes call them. You have to know the data science workflow, how do data scientists actually work? So understanding your users understanding how models should be deployed what deployment patterns exist. All these are things that if you come from a classic software engineer background, typically, this is something you have not quite seen, or you don't quite understand why somebody would work in an output crisis like Jupyter.

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