MLOps
Machine Learning Operations; the set of practices combining machine learning, DevOps and data engineering to reliably and efficiently deploy, manage and monitor ML models in production.
In plain language
The operational discipline of running AI in production; deploying, monitoring, updating and maintaining models reliably. It bridges the gap between building an AI in a lab and running it safely in the real world.
Why this matters
Robust MLOps is foundational to AI governance. Without MLOps capability, governance policies cannot be enforced consistently across the AI lifecycle, and organisations lose visibility over deployed models.
Relevance
GovernanceMLOps provides the operational infrastructure necessary to implement and audit governance requirements throughout a model's lifecycle.
Related terms
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