MLflow is the standard platform for experiment tracking and model management in data science teams.

Installation

pip install mlflow
mlflow ui

Browser: http://localhost:5000

Tracking API

import mlflow

mlflow.start_run()
mlflow.log_param("n_estimators", 100)
mlflow.log_metric("accuracy", 0.95)
mlflow.sklearn.log_model(model, "model")
mlflow.end_run()

Model Registry

mlflow.register_model(
    "runs:/abc123/model",
    "my-classifier"
)

# Promote to production
client = mlflow.tracking.MlflowClient()
client.transition_model_version_stage(
    name="my-classifier",
    version=1,
    stage="Production"
)

Serving

mlflow models serve -m runs:/abc123/model -p 1234

Sources