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Machine Learning with Amazon SageMaker Cookbook

You're reading from   Machine Learning with Amazon SageMaker Cookbook 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781800567030
Length 762 pages
Edition 1st Edition
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Author (1):
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Joshua Arvin Lat Joshua Arvin Lat
Author Profile Icon Joshua Arvin Lat
Joshua Arvin Lat
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Table of Contents (11) Chapters Close

Preface 1. Chapter 1: Getting Started with Machine Learning Using Amazon SageMaker 2. Chapter 2: Building and Using Your Own Algorithm Container Image FREE CHAPTER 3. Chapter 3: Using Machine Learning and Deep Learning Frameworks with Amazon SageMaker 4. Chapter 4: Preparing, Processing, and Analyzing the Data 5. Chapter 5: Effectively Managing Machine Learning Experiments 6. Chapter 6: Automated Machine Learning in Amazon SageMaker 7. Chapter 7: Working with SageMaker Feature Store, SageMaker Clarify, and SageMaker Model Monitor 8. Chapter 8: Solving NLP, Image Classification, and Time-Series Forecasting Problems with Built-in Algorithms 9. Chapter 9: Managing Machine Learning Workflows and Deployments 10. Other Books You May Enjoy

Preparing the Amazon S3 bucket and the training dataset for the linear regression experiment

In this recipe, we will create an Amazon S3 bucket using the AWS CLI within the Terminal. This S3 bucket will contain the input and output files when we are performing the different recipes in this chapter. If this is your first time hearing about Amazon S3, it is an object storage service that helps users store their files and their data. In the recipes in this book, we will store and download different files, datasets, and logs in Amazon S3 while we are working on our ML experiments. The AWS Command-Line Interface (CLI), on the other hand, is a command-line utility that helps to control and manage multiple AWS services and resources. In this recipe, we will use it to create an Amazon S3 bucket with the aws s3 mb command in the Terminal.

Important note

Note that most of the recipes in this book will store and load files inside the S3 bucket we will create in this recipe. Inside this...

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