title, type, tags, sources, last_updated
| title |
type |
tags |
sources |
last_updated |
| ML Ops |
concept |
| machine-learning |
| operations |
| lifecycle |
|
|
2026-04-20 |
Definition
ML Ops is the discipline of operationalizing machine learning models across development, deployment, monitoring, and governance.
Core Areas
- Data pipelines
- Training and deployment
- Monitoring and drift detection
- Governance and auditability
Relevance to Model QA
- Provides the operational context for audits
- Supplies monitoring and reproducibility artifacts
- Supports remediation and retraining loops
Related Concepts
