English | 2021 | ISBN-13 : 978-1484262214 | 258 Pages | PDF, EPUB| 15.26 MB

Successfully build, tune, deploy, and productionize any machine learning model, and know how to automate the process from data processing to deployment.

This book is divided into three parts. Part I introduces basic cloud concepts and teologies related to AWS services such as S3, EC2, Identity Access Management, Roles, Load Balancer, and Cloud Formation. It also covers cloud security topics such as AWS Compliance and artifacts, and the AWS Shield and CloudWatch monitoring service built for developers and DevOps eeers. Part II covers machine learning in AWS using SageMaker, which gives developers and data scientists the ability to build, train, and deploy machine learning models. Part III explores other AWS services such as Comprehend (a natural language processing service that uses machine learning to find insights and relationships in text), Forecast (helps you deliver accurate forecasts), and Textract.

By the end of the book, you will understand the machine learning pipeline and how to execute any machine learning model using AWS. The book will also help you prepare for the AWS Certified Machine Learning―Specialty certification exam.

What You Will Learn

Be familiar with the different machine learning services offered by AWS

Understand S3, EC2, Identity Access Management, and Cloud Formation

Understand SageMaker, Comprehend, and Forecast

Execute live projects: from the pre-processing phase to deployment on AWS

Who This Book Is For

Machine learning eeers who want to learn AWS machine learning services, and acquire an AWS machine learning specialty certification



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