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Practical Machine Learning on Databricks

You're reading from   Practical Machine Learning on Databricks Seamlessly transition ML models and MLOps on Databricks

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781801812030
Length 244 pages
Edition 1st Edition
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Author (1):
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Debu Sinha Debu Sinha
Author Profile Icon Debu Sinha
Debu Sinha
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Table of Contents (16) Chapters Close

Preface 1. Part 1: Introduction
2. Chapter 1: The ML Process and Its Challenges FREE CHAPTER 3. Chapter 2: Overview of ML on Databricks 4. Part 2: ML Pipeline Components and Implementation
5. Chapter 3: Utilizing the Feature Store 6. Chapter 4: Understanding MLflow Components on Databricks 7. Chapter 5: Create a Baseline Model Using Databricks AutoML 8. Part 3: ML Governance and Deployment
9. Chapter 6: Model Versioning and Webhooks 10. Chapter 7: Model Deployment Approaches 11. Chapter 8: Automating ML Workflows Using Databricks Jobs 12. Chapter 9: Model Drift Detection and Retraining 13. Chapter 10: Using CI/CD to Automate Model Retraining and Redeployment 14. Index 15. Other Books You May Enjoy

Understanding Databricks Workflows

Workflows in the simplest sense are frameworks for developing and running your data processing pipelines.

Databricks Workflows provides a reliable, fully managed orchestration service for all your data, analytics, and AI workloads on the Databricks Lakehouse platform on any cloud. Workflows are designed to ground up with the Databricks Lakehouse platform, providing deep monitoring capabilities along with centralized observability across all your other workflows. There is no additional cost to customers for using Databricks Workflows.

The key benefit of using workflows is that users don’t need to worry about managing orchestration software and infrastructure. Users can simply focus on specifying the business logic that needs to be executed as part of the workflows.

Within Databricks Workflows, there are two ways you can make use of the managed workflows:

  • Delta Live Tables (DLT): DLT is a declarative ETL framework to develop...
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