Machine learning (ML) projects often involve complex workflows, from data preprocessing and model training to deployment and monitoring. Managing these workflows efficiently is crucial for success. This is where Kedro-MLflow comes into play — a powerful integration of Kedro, a workflow orchestration tool, and MLflow, a platform for managing the ML lifecycle.

In this article, we’ll explore the Kedro-MLflow documentation (available as a PDF here) and highlight how this integration can simplify and enhance your ML workflows.