Automated Machine Learning on AWS: Fast-track the development of your production-ready machine learning applications the AWS way

AWS provides a wide range of solutions to help automate a machine learning workflow with just a few lines of code. With this practical book, you'll learn how to automate a machine learning pipeline using the various AWS services.
Automated Machine Learning on AWS begins with a quick overview of what the machine learning pipeline/process looks like and highlights the typical challenges that you may face when building a pipeline. Throughout the book, you'll become well versed with various AWS solutions such as Amazon SageMaker Autopilot, AutoGluon, and AWS Step Functions to automate an end-to-end ML process with the help of hands-on examples. The book will show you how to build, monitor, and execute a CI/CD pipeline for the ML process and how the various CI/CD services within AWS can be applied to a use case with the Cloud Development Kit (CDK). You'll understand what a data-centric ML process is by working with the Amazon Managed Services for Apache Airflow and then build a managed Airflow environment. You'll also cover the key success criteria for an MLSDLC implementation and the process of creating a self-mutating CI/CD pipeline using AWS CDK from the perspective of the platform engineering team.
By the end of this AWS book, you'll be able to effectively automate a complete machine learning pipeline and deploy it to production.

1140965852
Automated Machine Learning on AWS: Fast-track the development of your production-ready machine learning applications the AWS way

AWS provides a wide range of solutions to help automate a machine learning workflow with just a few lines of code. With this practical book, you'll learn how to automate a machine learning pipeline using the various AWS services.
Automated Machine Learning on AWS begins with a quick overview of what the machine learning pipeline/process looks like and highlights the typical challenges that you may face when building a pipeline. Throughout the book, you'll become well versed with various AWS solutions such as Amazon SageMaker Autopilot, AutoGluon, and AWS Step Functions to automate an end-to-end ML process with the help of hands-on examples. The book will show you how to build, monitor, and execute a CI/CD pipeline for the ML process and how the various CI/CD services within AWS can be applied to a use case with the Cloud Development Kit (CDK). You'll understand what a data-centric ML process is by working with the Amazon Managed Services for Apache Airflow and then build a managed Airflow environment. You'll also cover the key success criteria for an MLSDLC implementation and the process of creating a self-mutating CI/CD pipeline using AWS CDK from the perspective of the platform engineering team.
By the end of this AWS book, you'll be able to effectively automate a complete machine learning pipeline and deploy it to production.

39.99 In Stock
Automated Machine Learning on AWS: Fast-track the development of your production-ready machine learning applications the AWS way

Automated Machine Learning on AWS: Fast-track the development of your production-ready machine learning applications the AWS way

Automated Machine Learning on AWS: Fast-track the development of your production-ready machine learning applications the AWS way

Automated Machine Learning on AWS: Fast-track the development of your production-ready machine learning applications the AWS way

eBook

$39.99 

Available on Compatible NOOK devices, the free NOOK App and in My Digital Library.
WANT A NOOK?  Explore Now

Related collections and offers


Overview

AWS provides a wide range of solutions to help automate a machine learning workflow with just a few lines of code. With this practical book, you'll learn how to automate a machine learning pipeline using the various AWS services.
Automated Machine Learning on AWS begins with a quick overview of what the machine learning pipeline/process looks like and highlights the typical challenges that you may face when building a pipeline. Throughout the book, you'll become well versed with various AWS solutions such as Amazon SageMaker Autopilot, AutoGluon, and AWS Step Functions to automate an end-to-end ML process with the help of hands-on examples. The book will show you how to build, monitor, and execute a CI/CD pipeline for the ML process and how the various CI/CD services within AWS can be applied to a use case with the Cloud Development Kit (CDK). You'll understand what a data-centric ML process is by working with the Amazon Managed Services for Apache Airflow and then build a managed Airflow environment. You'll also cover the key success criteria for an MLSDLC implementation and the process of creating a self-mutating CI/CD pipeline using AWS CDK from the perspective of the platform engineering team.
By the end of this AWS book, you'll be able to effectively automate a complete machine learning pipeline and deploy it to production.


Product Details

ISBN-13: 9781801814522
Publisher: Packt Publishing
Publication date: 04/15/2022
Sold by: Barnes & Noble
Format: eBook
Pages: 420
File size: 10 MB
From the B&N Reads Blog

Customer Reviews