End-to-end ML pipeline on Azure Machine Learning for heart disease prediction. Features 4-step automated workflow (data prep, training, evaluation, registration), MLflow experiment tracking, and managed endpoint deployment. Built with Azure ML SDK v2, scikit-learn, and auto-scaling compute clusters.

Production-grade ML pipeline built with the Azure ML SDK covering dataset registration, compute cluster provisioning, cloud training, model registry, and real-time REST API deployment. Cloud-trained ROC AUC of 0.8313 matching local results.