IT AI Skill

Mlops Model Ops

Implement MLOps practices for machine learning lifecycle management including model training, versioning, deployment, monitoring, and retraining. Use when building ML pipelines, managing model versions, deploying models to production, monitoring model drift, or automating retraining workflows. Triggers on phrases like "MLOps", "model deployment", "model monitoring", "model drift", "feature store", "model registry", "ML pipeline", "retraining", "A/B testing models", "model versioning", "experiment tracking", "model serving", "inference", "training pipeline".