Glossary
MLOps
Definition
MLOps is the set of practices for deploying, monitoring, and maintaining machine-learning systems in production reliably, the discipline that keeps AI working after launch.
Last updated
Key points
- Covers deployment, monitoring, retraining, and performance tracking.
- Prevents the silent model decay that degrades accuracy over time.
- The difference between a model in a notebook and a system that serves users.
Related:Lightweight AI Infrastructure
Quick answer
MLOps, common question
Because real-world data shifts, model accuracy drifts without monitoring and occasional retraining. MLOps is what keeps a deployed system trustworthy instead of quietly degrading.
From concept to working product.
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