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

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Himanshu Singh Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS
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Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS: summary, description and annotation

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Himanshu Singh: author's other books


Who wrote Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS? Find out the surname, the name of the author of the book and a list of all author's works by series.


Himanshu Singh - Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS
Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS
Himanshu Singh
Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS
Himanshu Singh - Practical Machine Learning and Image Processing
Practical Machine Learning and Image Processing
Himanshu Singh
Practical Machine Learning and Image Processing
No cover
No cover
Himanshu Singh
Statistics for Machine Learning: Implement Statistical methods used in Machine Learning using Python

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Book cover of Practical Machine Learning with AWS Himanshu Singh - photo 1
Book cover of Practical Machine Learning with AWS
Himanshu Singh
Practical Machine Learning with AWS
Process, Build, Deploy, and Productionize Your Models Using AWS
1st ed.
Logo of the publisher Himanshu Singh ALLAHABAD Uttar Pradesh India Any - photo 2
Logo of the publisher
Himanshu Singh
ALLAHABAD, Uttar Pradesh, India

Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub via the books product page, located at www.apress.com/978-1-4842-6221-4 . For more detailed information, please visit www.apress.com/source-code .

ISBN 978-1-4842-6221-4 e-ISBN 978-1-4842-6222-1
https://doi.org/10.1007/978-1-4842-6222-1
Himanshu Singh 2021
Apress Standard
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Distributed to the book trade worldwide by Springer Science+Business Media New York, 1 New York Plaza, Suite 4600, New York, NY 10004-1562, USA. Phone 1-800-SPRINGER, fax (201) 348-4505, e-mail orders-ny@springer-sbm.com, or visit www.springeronline.com. Apress Media, LLC is a California LLC and the sole member (owner) is Springer Science + Business Media Finance Inc (SSBM Finance Inc). SSBM Finance Inc is a Delaware corporation.
Introduction

This book is structured into three parts. The first part of the book covers the concepts of cloud computing and gives an overview of how AWS works. The second part of the book takes on AWS in detail and covers SageMaker, Step Functions, S3 buckets, ECR, etc. The last part talks about the use cases for AWS services. Different services such as Amazon Comprehend and Extract are discussed here.

Specifically, Part I starts by covering cloud terminologies. It helps you understand the cloud concepts required to use AWS. Then the book discusses the various AWS services that Amazon provides and how they help users in different ways. It discusses the different functionalities of AWS that are categorized under storage-based, compute-based, security-based, etc. By end of the chapters in this part, you will have an overview of how AWS works.

Part II discusses SageMaker in detail. The part starts by running a basic preprocessing script in SageMaker and ends with building a complete end-to-end pipeline of machine learning in it. It covers how SageMaker talks with different services such as ECR, S3, Step Functions, etc., to build the final model.

Part III discusses three use cases of machine learning using some of the other services of AWS. The book discusses how to extract text using Amazon Textract, how to use Amazon Comprehend, and how to make a time-series model using Amazon Forecast.

This book was written to give people who know Python and machine learning some experience with AWS. It teaches you how to use the power of AWS to build your heavy models and how AWS provides you with services to make super models or deploy your custom code with the same AWS support.

Acknowledgments

Id like to thank my parents and brother for their unbounded support and the Apress-Springer team.

Table of Contents
Part I: Introduction to Amazon Web Services
Part II: Machine Learning in AWS
Part III: Other AWS Services
About the Author
Himanshu Singh
is a technology lead and senior NLP engineer at Legato Healthcare an Anthem - photo 3

is a 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.

About the Technical Reviewer
Anindita Basak
is a cloud architect and DevOps engineer With more than a decade of - photo 4

is a cloud architect and DevOps engineer. With more than a decade of experience, she helps enterprises to enable their digital transformation journey empowered with multicloud, DevOps, advanced analytics, and AI. She co-authored the books Stream Analytics with Microsoft Azure and Hands-on Azure Machine Learning and was a technical reviewer of seven books on Azure along with two video courses on Azure data analytics. She has also worked extensively with AWS Infra, DevOps, and analytics.

Part I Introduction to Amazon Web Services
Himanshu Singh 2021
H. Singh Practical Machine Learning with AWS https://doi.org/10.1007/978-1-4842-6222-1_1
1. Cloud Computing and AWS
Himanshu Singh
(1)
ALLAHABAD, Uttar Pradesh, India

This chapter covers the different components of cloud computing and of Amazon Web Services (AWS). After reading the chapter, youll understand the different important components of AWS, which will make it easier to understand the machine learning components of AWS.

What Is the Cloud?

So, what is the cloud? If you look at memes shared across the internet, you might think the cloud is nothing but someone elses computer that you can use from your own computing device, for your own personal use. Then the question arises, why do we need the other computer when we have our own? Its because our computer may not have things that the other system has. Maybe your budget when buying a system was less than the other persons, and he therefore has more computational power to use. So, instead of buying a new system with more computational power, you can just access the other system for some amount of time and then return to your own system. This is the benefit that the cloud provides. And, by the way, we all know the other system is not just any normal system. Cloud systems are provided by big companies such as Amazon and Google. So even if you are trying to buy a new system with as much computational power as cloud systems, you will not be able to afford it.

Formally speaking, the cloud is a particular computing service that is present at a different remote location that we can access using networking or the internet. Cloud services may include storage services, infrastructure services, software services, or any other specific services that you need. Figure shows how different devices are connected to cloud systems at a remote location.
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