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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

Onboarding to SageMaker Studio

Amazon SageMaker Studio is a fully integrated environment for machine learning. With SageMaker Studio, we can easily use the other features and capabilities of SageMaker in this environment, such as SageMaker Autopilot, SageMaker Debugger, and SageMaker Experiments, using its intuitive user interface. In this recipe, we will set up SageMaker Studio so that we can use its different features and integrations in the succeeding recipes. We will assume that this is your first time using SageMaker Studio, so we will work on setting up the execution roles and other prerequisites in this recipe as well.

In the Creating and monitoring a SageMaker Autopilot experiment in SageMaker Studio (console) recipe, we will see how easy it is to create an Autopilot experiment using SageMaker Studio without having to write a single line of code. For now, we will be focusing on getting our environment set up so that we can use it in the subsequent recipes.

Note

Using...

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