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

Product type Paperback

Published in Oct 2021

Publisher Packt

ISBN-13 9781800567030

Length 762 pages

Edition 1st Edition

Languages

Python

Tools

AWS

Concepts

Machine Learning

Author (1):

Joshua Arvin Lat

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

Technical requirements

You will need the following to complete the recipes in this chapter:

A running Amazon SageMaker notebook instance (for example, ml.t2.large). Feel free to use the SageMaker notebook instance we launched in the Launching an Amazon SageMaker Notebook instance recipe of Chapter 1, Getting Started with Machine Learning Using Amazon SageMaker.
Permission to manage the Amazon SageMaker, Amazon S3, and AWS Cloud9 resources if you're using an AWS IAM user with a custom URL. It is recommended to be signed in as an AWS IAM user instead of using the root account in most cases. For more information, feel free to take a look at https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html.

The Jupyter Notebooks, source code, and CSV files used for each chapter are available in this book's GitHub repository: https://github.com/PacktPublishing/Machine-Learning-with-Amazon-SageMaker-Cookbook/tree/master/Chapter02.

Check out the following link to see the relevant Code in Action video: