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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

Summary

This chapter covered a wide range of setup decisions, options, and processes for planning your Data Intelligence Platform. We took you through an overview of the main components of the DI Platform, from early design choices to important features that we will dive into further in upcoming chapters. You also learned how to set up your workspace and project code base. We hope you feel more comfortable with the basics of the platform. With Databricks ready and the project data downloaded, we are now ready to get into what it means to build out the Bronze data layer.

In Chapter 3, we cover the essentials of building out the Bronze data layer within the Databricks Intelligence Platform. We will format our data into the most optimized format, learn about schema evolution, change data capture using Delta, and more.

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