From model-centric to data-centric MLOps | Ubuntu

MLOps (short for machine learning operations) is slowly evolving into an independent approach to the machine learning lifecycle that includes all steps – from data gathering to governance and monitoring. It will become a standard as artificial intelligence is moving towards becoming part of everyday business, rather than an innovative activity. 

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Over time, there have been different approaches used in MLOps. The most popular ones are model-driven and data-driven approaches. The split between them is defined by the main focus of the AI system: data or code. Which one should you choose? The decision challenges data scientists to choose which component will play a more important role in the development of a robust model. In this blog, we will evaluate both.

Model-centric development

Model-driven development focuses, as the name suggests, on machine learning model performance. It uses…

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