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Serverless Machine Learning with Amazon Redshift ML
Serverless Machine Learning with Amazon Redshift ML

Serverless Machine Learning with Amazon Redshift ML: Create, train, and deploy machine learning models using familiar SQL commands

By Debu Panda , Phil Bates , Bhanu Pittampally , Sumeet Joshi
$15.99 per month
Book Aug 2023 290 pages 1st Edition
eBook
$39.99 $9.99
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$49.99
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eBook
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Product Details


Publication date : Aug 30, 2023
Length 290 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781804619285
Category :
Table of content icon View table of contents Preview book icon Preview Book

Serverless Machine Learning with Amazon Redshift ML

Part 1:Redshift Overview: Getting Started with Redshift Serverless and an Introduction to Machine Learning

Reaping the benefits of machine learning across an organization requires access to data, easy-to-use tools, and built-in algorithms that anyone can use no matter their level of experience with machine learning.

Part 1 shows how easy it is to get started with Amazon Redshift Serverless and Amazon Redshift ML without having to manage data warehouse infrastructure.

By the end of Part 1, you will know how to run queries using Query Editor v2 notebooks and different techniques for loading data into Amazon Redshift Serverless. You will then be introduced to machine learning and gain an understanding of how you can use machine learning in your data warehouse.

This part comprises the following chapters:

  • Chapter 1, Introduction to Amazon Redshift Serverless
  • Chapter 2, Data Loading and Analytics on Redshift Serverless
  • Chapter 3, Applying Machine Learning in Your...
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Key benefits

  • Leverage supervised learning to build binary classification, multi-class classification, and regression models
  • Learn to use unsupervised learning using the K-means clustering method
  • Master the art of time series forecasting using Redshift ML
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

Amazon Redshift Serverless enables organizations to run petabyte-scale cloud data warehouses quickly and in a cost-effective way, enabling data science professionals to efficiently deploy cloud data warehouses and leverage easy-to-use tools to train models and run predictions. This practical guide will help developers and data professionals working with Amazon Redshift data warehouses to put their SQL knowledge to work for training and deploying machine learning models. The book begins by helping you to explore the inner workings of Redshift Serverless as well as the foundations of data analytics and types of data machine learning. With the help of step-by-step explanations of essential concepts and practical examples, you’ll then learn to build your own classification and regression models. As you advance, you’ll find out how to deploy various types of machine learning projects using familiar SQL code, before delving into Redshift ML. In the concluding chapters, you’ll discover best practices for implementing serverless architecture with Redshift. By the end of this book, you’ll be able to configure and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale.

What you will learn

Utilize Redshift Serverless for data ingestion, data analysis, and machine learning Create supervised and unsupervised models and learn how to supply your own custom parameters Discover how to use time series forecasting in your data warehouse Create a SageMaker endpoint and use that to build a Redshift ML model for remote inference Find out how to operationalize machine learning in your data warehouse Use model explainability and calculate probabilities with Amazon Redshift ML

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Product Details


Publication date : Aug 30, 2023
Length 290 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781804619285
Category :

Table of Contents

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

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