What is MLflow?
MLflow is the industry-standard open-source platform for managing the ML lifecycle — experiment tracking, model registry, deployment, and evaluation. Log parameters, metrics, and models from any ML framework. Compare experiments visually. Promote models to production through a registry with versioning.
Quick start
1
pip install mlflow 2
mlflow ui # Open http://localhost:5000 3
import mlflow; mlflow.start_run() 4
mlflow.log_param("lr", 0.01) 5
mlflow.log_metric("accuracy", 0.92) Use cases
→Experiment tracking
→Model versioning
→Model registry
→Reproducible ML
Compatible models
Framework agnostic — works with sklearn, PyTorch, TensorFlow, XGBoost etc.
Why this matters for India
// india context
Standard tool in Indian ML/data science teams. Knowing MLflow is expected in most MLOps job descriptions.