
Databricks MLOps: How to Build Production-Ready ML Pipelines
TL;DR Databricks MLOps is the practice of operationalizing machine learning on the Databricks Lakehouse platform, covering the full lifecycle from data ingestion and feature engineering through model training, versioned deployment, and ongoing monitoring. It uses four core components: Delta Lake for governed data storage, MLflow for experiment tracking and model registry, Unity Catalog for centralized access control and lineage, and







