From Notebook to Production: End-to-End MLOps on Databricks

Move beyond Jupyter notebooks and deploy machine learning models to production using MLOps best practices on Databricks. In this intermediate workshop, you'll learn to structure ML projects for production, implement CI/CD pipelines for models, manage experiments with MLflow, deploy models as REST APIs, and monitor them in production. We'll walk through a complete end-to-end example from data preparation to automated retraining.