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MLOps
Tech & Tools
Operational practices for managing machine learning lifecycle.
MLOps combines DevOps principles with machine learning workflows. It covers automation, version control, and monitoring for model lifecycle management.
- Components: CI/CD pipelines, model registry, feature store, monitoring.
- Goal: Ensure reproducible, reliable, and scalable AI systems.