Practical Data Science on Databricks: Scaling end-to-end machine learning on Databricks

Databricks ML Development and Deployment is a comprehensive guide that will help you unlock the full potential of Azure Databricks for data science applications.

With this book, you'll learn how to develop and productionize machine learning pipelines using the Databricks Unified Analytics platform, including AutoML, Feature Stores, and MLOps.

You'll gain hands-on experience implementing repeatable ML operations (MLOps) pipeline using MLFlow, tracking model training and key metrics, and exploring real-time ML, anomaly detection, and streaming analytics with Delta lake and Spark Structured Streaming.

By the end of the book, you will know how to set up your Databricks ML development and deployment as a CI/CD pipeline.

Whether you're new to data science or an experienced professional looking to enhance your skills, this book is perfect for anyone interested in leveraging Azure Databricks for their data science applications.