Databricks ML in Action
Learn how Databricks supports the entire ML lifecycle end to end from data ingestion to the model deployment
AB+1Created by Stephanie Rivera, Hayley Horn, Amanda Baker and 1 more
Get hands-on with the Databricks Data Intelligence Platform and learn how to manage the entire machine learning lifecycle. You'll work with real-world projects covering data ingestion, model training, and deployment, including streaming, forecasting, and generative AI tasks.
Packt | May 2024 | 280 min
What You Will Learn
You'll build practical skills by working through guided projects that mirror real industry scenarios. Each section focuses on applying Databricks tools to solve common machine learning challenges, helping you develop confidence as you progress from setup to deployment. Self-assessment checkpoints reinforce your understanding along the way.
Key Features
- Set up collaborative workspaces and monitor data quality for robust ML workflows
- Leverage AutoML, feature engineering, and managed tools to streamline model development
- Deploy, share, and operationalize models using Databricks SQL dashboards and Delta Sharing
Target Audience
Designed for machine learning engineers, data scientists, and technical managers with some experience in ML or data platforms. If you're looking to deepen your practical skills and deliver production-ready data products using Databricks, you'll find clear guidance and actionable techniques throughout.
