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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
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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

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

access control lists (ACLs) 4

AI Functions 231

analysts, with SQL AI Functions

LLMs, incorporating 231-235

applications

models, connecting to 231

Auto Loader 49

schema evolution 51

used, for transforming data to Delta 50, 51

Auto Loader, with DLT

used, for continuous data ingestion 60

Auto Loader, with Structured Streaming

used, for continuous data ingestion 58-60

automated machine learning (AutoML) 79, 141

baselining with 143, 144

data profiles, generating with 88-90

used, for creating baseline model 154-157

experiments, tracking with MLflow 144-147

Azure Data Lake Storage (ADLS) 23

B

batch feature 112

Bronze data

with DLT 53

bronze table

generating, in DLT pipeline 63

C

change data capture (CDC) 9

change data feed...

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