Azure Databricks for Scalable MLOps and Feature Engineering With Apache Spark, Delta Lake, and MLflow

Raw data doesn't win model competitions. Features do. And when your raw data is tens of billions of rows sitting across multiple sources, you can't afford to run pandas in a notebook and call it a day.

In this tutorial, I'll walk through building a production-grade feature engineering pipeline on Azure Databricks using: