mlflowintermediate30 min

MLflow + model registry management

Centralized model lifecycle management enabling team collaboration, versioning, staging/promotion, lineage tracking, and production deployment in AI agent pipelines.

Prerequisites

→Python 3.8+
→pip install mlflow scikit-learn
→MLflow tracking server (mlflow server --backend-store-uri sqlite:///mydb.db --default-artifact-root ./mlruns)
→basic MLflow familiarity.

Tools used

mlflow→