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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

Preparing the entrypoint TensorFlow and Keras training script

TensorFlow is a popular open source software library for machine learning. Keras, on the other hand, is a user-friendly high-level neural network library that helps build and train models faster.

In this recipe, we will define a custom TensorFlow and Keras neural network model and prepare the entrypoint training script. In the next recipe, we will use the TensorFlow estimator class from the SageMaker Python SDK with this script as the entrypoint argument for training and deployment. If you are planning to migrate your custom TensorFlow and Keras neural network code from your local machine and perform training and deployment with the SageMaker platform, then this recipe (and the next) is for you!

Getting ready

This recipe continues from Generating a synthetic dataset for deep learning experiments.

How to do it

The instructions in this recipe focus on preparing the entrypoint script. Let's start by creating...

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