databricks-ml-pipeline

What problem does it solve?

Orchestrates end-to-end ML workflows on Databricks, reducing manual integration and ensuring reproducible results across data exploration, feature engineering, model training, MLflow tracking, model registration to Unity Catalog, and production deployment as Databricks Asset Bundles.

Core Features & Use Cases

• End-to-end ML workflow orchestration: from data profiling to model deployment.
• Experiment tracking and model registry: integrate MLflow and Unity Catalog for reproducibility and governance.
• Production-ready packaging: deploy as Databricks Asset Bundles with scheduled retraining.
• Real-world scenarios include churn prediction, fraud detection, and customer segmentation pipelines.

Quick Start

Start by invoking the complete ML pipeline builder to coordinate exploration, training, and deployment on Databricks.