Introduction:
Machine learning projects often involve multiple stages, including data preprocessing, model training, hyperparameter tuning, and model deployment. Managing and tracking these stages can become complex and time-consuming. MLflow, an open-source machine learning platform, simplifies the end-to-end machine learning lifecycle by providing tools for experiment tracking, model packaging, and deployment.