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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

Checking the versions of the SageMaker Python SDK and the AWS CLI

In this recipe, we will check the SageMaker Python SDK version inside a notebook running the conda_python3 kernel. The SageMaker Python SDK is a library that helps data scientists and ML practitioners to train and deploy ML models on Amazon SageMaker. Knowing the version of this is critical as there are several differences between Version 1.X and Version 2.X of the SageMaker Python SDK. In this book, we will use Version 2.X.

Getting ready

Make sure you have completed the Launching an Amazon SageMaker notebook instance and preparing the prerequisites recipe.

How to do it…

The first set of steps in this recipe focus on checking the SageMaker Python SDK version:

  1. Click New and then choose conda_python3 in the drop-down list:

    Figure 1.17 – Creating a new notebook using the conda_python3 kernel

    We can see in Figure 1.17 that there are several environments to choose from when creating a new...

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