Dr. Paul Elvers: Getting Started with MLOps: Best Practices for Production-Ready ML Systems | PyData

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MLOps (ML + DevOps) describes the necessary practices & techniques for maintaining machine learning (ML) models in production. Thinking about machine learning from an MLOps-perspective shifts the focus of attention towards how models behave “in the wild” rather than optimising the model performance on a recognised training data set (e.g. MNIST) in ml-research. Thinking of ML from an MLOps-perspective is crucial for a successful use of machine learning in any business. I present the core concepts of MLOps and share insights about useful tools and technologies for building a minimal working ML system.

About Dr. Paul Elvers

Dr. Paul Elvers is Head of AI/Data Science at Datadrivers, an IT Consulting Company in Hamburg. He graduated in Systematic Musicology & worked as a Research Fellow at the Max-Planck-Institute for empirical Aesthetics.

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