Practical Machine Learning with AWS

1. Front Matter

   Pages i-xvii

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2. Introduction to Amazon Web Services

   1. Front Matter

      Pages 1-1

      PDF

   2. Cloud Computing and AWS

      • Himanshu Singh

      Pages 3-28

   3. AWS Pricing and Cost Management

      • Himanshu Singh

      Pages 29-44

   4. Security in Amazon Web Services

      • Himanshu Singh

      Pages 45-62

3. Machine Learning in AWS

   1. Front Matter

      Pages 63-63

      PDF

   2. Introduction to Machine Learning

      • Himanshu Singh

      Pages 65-88

   3. Data Processing in AWS

      • Himanshu Singh

      Pages 89-117

   4. Building and Deploying Models in SageMaker

      • Himanshu Singh

      Pages 119-154

   5. Using CloudWatch with SageMaker

      • Himanshu Singh

      Pages 155-165

   6. Running a Custom Algorithm in SageMaker

      • Himanshu Singh

      Pages 167-188

   7. Making an End-to-End Pipeline in SageMaker

      • Himanshu Singh

      Pages 189-203

4. Other AWS Services

   1. Front Matter

      Pages 205-205

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   2. Machine Learning Use Cases in AWS

      • Himanshu Singh

      Pages 207-225

5. Back Matter

   Pages 227-241

   PDF

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.




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, Amazon Comprehend, and Amazon Forecast
  
• Execute live projects: from the pre-processing phase to deployment on AWS
  

Who This Book Is For




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

• AWS Machine Learning
• AWS Sagemaker
• AWS Firehose
• AWS Kinesis
• AWS EMR
• AWS EC2
• AWS Lambda Function
• AWS Blazing Text
• AWS Deep Razor

• ALLAHABAD, India

  Himanshu Singh

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.

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