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Databricks ML in Action

You're reading from   Databricks ML in Action Learn how Databricks supports the entire ML lifecycle end to end from data ingestion to the model deployment

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781800564893
Length 280 pages
Edition 1st Edition
Languages
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Authors (4):
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Hayley Horn Hayley Horn
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Hayley Horn
Amanda Baker Amanda Baker
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Amanda Baker
Anastasia Prokaieva Anastasia Prokaieva
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Anastasia Prokaieva
Stephanie Rivera Stephanie Rivera
Author Profile Icon Stephanie Rivera
Stephanie Rivera
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Toc

Table of Contents (13) Chapters Close

Preface 1. Part 1: Overview of the Databricks Unified Data Intelligence Platform FREE CHAPTER
2. Chapter 1: Getting Started and Lakehouse Concepts 3. Chapter 2: Designing Databricks: Day One 4. Chapter 3: Building the Bronze Layer 5. Part 2: Heavily Project Focused
6. Chapter 4: Getting to Know Your Data 7. Chapter 5: Feature Engineering on Databricks 8. Chapter 6: Tools for Model Training and Experimenting 9. Chapter 7: Productionizing ML on Databricks 10. Chapter 8: Monitoring, Evaluating, and More 11. Index 12. Other Books You May Enjoy

Deploying the MLOps outer loop

The ML life cycle looks different for different use cases. However, the set of tools available in the Databricks platform makes it possible to automate as you like and supports your MLOps. The outer loop connects the inner loop products with the help of Workflows, Databricks Terraform Provider, REST API, DABs, and more. We covered automating the tracking process through MLflow Tracking and the UC Registry. The UC Registry is tightly integrated with the Model Serving feature and has a robust API that can easily be integrated into the automation process using webhooks. Each of these features can play a role in automating the ML life cycle.

Workflows

Databricks Workflows is a flexible orchestration tool for productionizing and automating ML projects. Workflows help the ML life cycle by providing a unified way to chain together all aspects of ML, from data preparation to model deployment. With Databricks Workflows, you can designate dependencies between...

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