25 lines
643 B
Markdown
25 lines
643 B
Markdown
---
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title: "ML Ops"
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type: concept
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tags: [machine-learning, operations, lifecycle]
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sources: [specialized-model-qa]
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last_updated: 2026-04-20
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---
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## Definition
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ML Ops is the discipline of operationalizing machine learning models across development, deployment, monitoring, and governance.
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## Core Areas
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- Data pipelines
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- Training and deployment
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- Monitoring and drift detection
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- Governance and auditability
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## Relevance to Model QA
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- Provides the operational context for audits
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- Supplies monitoring and reproducibility artifacts
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- Supports remediation and retraining loops
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## Related Concepts
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- [[Model Audit]]
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- [[Discrimination Metrics]] |