databricks-ml

What problem does it solve?

This Skill streamlines the end-to-end machine learning lifecycle on Databricks, from experiment tracking and model registration to CI/CD deployment and monitoring.

Core Features & Use Cases

• MLflow Integration: Comprehensive experiment tracking, model registry, and artifact logging.
• Feature Store & Unity Catalog: Seamlessly manage features and models with robust governance.
• Databricks Asset Bundles: Automate ML pipelines with infrastructure-as-code and CI/CD.
• Use Case: Deploy a customer churn prediction model from development to production using automated CI/CD pipelines, ensuring reproducibility and governance.

Quick Start

Use the databricks-ml skill to set up a new MLflow experiment for your project.