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Serverless Machine Learning with Amazon Redshift ML

You're reading from   Serverless Machine Learning with Amazon Redshift ML Create, train, and deploy machine learning models using familiar SQL commands

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Product type Paperback
Published in Aug 2023
Publisher Packt
ISBN-13 9781804619285
Length 290 pages
Edition 1st Edition
Languages
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Authors (4):
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Phil Bates Phil Bates
Author Profile Icon Phil Bates
Phil Bates
Sumeet Joshi Sumeet Joshi
Author Profile Icon Sumeet Joshi
Sumeet Joshi
Debu Panda Debu Panda
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Debu Panda
Bhanu Pittampally Bhanu Pittampally
Author Profile Icon Bhanu Pittampally
Bhanu Pittampally
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1:Redshift Overview: Getting Started with Redshift Serverless and an Introduction to Machine Learning
2. Chapter 1: Introduction to Amazon Redshift Serverless FREE CHAPTER 3. Chapter 2: Data Loading and Analytics on Redshift Serverless 4. Chapter 3: Applying Machine Learning in Your Data Warehouse 5. Part 2:Getting Started with Redshift ML
6. Chapter 4: Leveraging Amazon Redshift ML 7. Chapter 5: Building Your First Machine Learning Model 8. Chapter 6: Building Classification Models 9. Chapter 7: Building Regression Models 10. Chapter 8: Building Unsupervised Models with K-Means Clustering 11. Part 3:Deploying Models with Redshift ML
12. Chapter 9: Deep Learning with Redshift ML 13. Chapter 10: Creating a Custom ML Model with XGBoost 14. Chapter 11: Bringing Your Own Models for Database Inference 15. Chapter 12: Time-Series Forecasting in Your Data Warehouse 16. Chapter 13: Operationalizing and Optimizing Amazon Redshift ML Models 17. Index 18. 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

accuracy 53, 91

Amazon Forecast 224, 225

model accuracy metrics 227

AmazonForecastFullAccess managed policy 225

Amazon Redshift 4

Amazon Redshift Data API 43

data loading 43, 44, 47, 48

table, creating 45-47

Amazon Redshift ML 63-65, 158

data, analyzing 80-84

data, uploading 80-84

Amazon Redshift query editor v2 14, 25, 26

used, for connecting to data warehouse 14-16

Amazon Redshift Serverless 5-8, 25

Amazon Resource Name (ARN) 242

Amazon SageMaker 9, 63, 65

Amazon SageMaker Random Cut Forest model

BYOM remote inference, creating for 213, 214

Amazon Simple Storage Service (Amazon S3) 3, 9, 68

Amazon Web Services (AWS) 5

API 6

area under the curve (AUC) 53, 54, 91

artificial intelligence (AI) 174

artificial neural network (ANN...

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