Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS

  • 2h 25m
  • Himanshu Singh
  • Apress
  • 2021

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 terminologies 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 engineers. 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 Amazon Comprehend (a natural language processing service that uses machine learning to find insights and relationships in text), Amazon Forecast (helps you deliver accurate forecasts), and Amazon 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.

You will:

  • Be familiar with the different machine learning services offered by AWS
  • Understand S3, EC2, Identity Access Management, and Cloud Formation
  • Understand SageMaker, Amazon Comprehend, and Amazon Forecast
  • Execute live projects: from the pre-processing phase to deployment on AWS

About the Author

Himanshu Singh is Technology Lead and Senior NLP Engineer at Legato Healthcare (an Anthem Company). He has seven years of experience in the AI industry, primarily in computer vision and natural language processing. He has authored three books on machine learning. He has an MBA from Narsee Monjee Institute of Management Studies, and a postgraduate diploma in Applied Statistics.

In this Book

  • Cloud Computing and AWS
  • AWS Pricing and Cost Management
  • Security in Amazon Web Services
  • Introduction to Machine Learning
  • Data Processing in AWS
  • Building and Deploying Models in SageMaker
  • Using CloudWatch with SageMaker
  • Running a Custom Algorithm in SageMaker
  • Making an End-to-End Pipeline in SageMaker
  • Machine Learning Use Cases in AWS

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