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

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

Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Learn Amazon SageMaker – Second Edition

Julien Simon

ISBN: 978-1-80181-795-0

Become well-versed with data annotation and preparation techniques
Use AutoML features to build and train machine learning models with AutoPilot
Create models using built-in algorithms and frameworks and your own code
Train computer vision and natural language processing (NLP) models using real-world examples
Cover training techniques for scaling, model optimization, model debugging, and cost optimization
Automate deployment tasks in a variety of configurations using SDK and several automation tools

Machine Learning with Amazon SageMaker Cookbook

Joshua Arvin Lat

ISBN: 978-1-80056-703-0