You're reading from Getting Started with Amazon SageMaker Studio Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE

Product type Paperback

Published in Mar 2022

Publisher Packt

ISBN-13 9781801070157

Length 326 pages

Edition 1st Edition

Languages

Python

Concepts

Machine Learning

Author (1):

Michael Hsieh

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Table of Contents (16) Chapters

Preface

1. Part 1 – Introduction to Machine Learning on Amazon SageMaker Studio

2. Chapter 1: Machine Learning and Its Life Cycle in the Cloud FREE CHAPTER

3. Chapter 2: Introducing Amazon SageMaker Studio

4. Part 2 – End-to-End Machine Learning Life Cycle with SageMaker Studio

5. Chapter 3: Data Preparation with SageMaker Data Wrangler

6. Chapter 4: Building a Feature Repository with SageMaker Feature Store

7. Chapter 5: Building and Training ML Models with SageMaker Studio IDE

8. Chapter 6: Detecting ML Bias and Explaining Models with SageMaker Clarify

9. Chapter 7: Hosting ML Models in the Cloud: Best Practices

10. Chapter 8: Jumpstarting ML with SageMaker JumpStart and Autopilot

11. Part 3 – The Production and Operation of Machine Learning with SageMaker Studio

12. Chapter 9: Training ML Models at Scale in SageMaker Studio

13. Chapter 10: Monitoring ML Models in Production with SageMaker Model Monitor

14. Chapter 11: Operationalize ML Projects with SageMaker Projects, Pipelines, and Model Registry

15. Other Books You May Enjoy

Part 3 – The Production and Operation of Machine Learning with SageMaker Studio

In this section, you will learn how to effectively scale and operationalize the machine learning (ML) life cycle using SageMaker Studio so that you can reduce the amount of manual and undifferentiating work needed from a data scientist and allow them to focus on modeling.

This section comprises the following chapters:

Chapter 9, Training ML Models at Scale in SageMaker Studio
Chapter 10, Monitoring ML Models in Production with SageMaker Model Monitoring
Chapter 11, Operationalize ML Projects with SageMaker Projects, Pipelines, and Model Registry

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You're reading from Getting Started with Amazon SageMaker Studio Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE

Table of Contents (16) Chapters

Part 3 – The Production and Operation of Machine Learning with SageMaker Studio

Authors (1)

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You're reading from Getting Started with Amazon SageMaker Studio Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE

Table of Contents (16) Chapters

Part 3 – The Production and Operation of Machine Learning with SageMaker Studio

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Authors (1)

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