Hands-On Artificial Intelligence on Amazon Web Services

coverpage

Title Page

Copyright and Credits

Hands-On Artificial Intelligence on Amazon Web Services

About Packt

Why subscribe?

Contributors

About the authors

About the reviewer

Packt is searching for authors like you

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Download the color images

Conventions used

Get in touch

Reviews

Section 1: Introduction and Anatomy of a Modern AI Application

Introduction to Artificial Intelligence on Amazon Web Services

Technical requirements

What is AI?

Applications of AI

Autonomous vehicles

AI in medical care

Personalized predictive keyboards

Why use Amazon Web Services for AI?

Overview of AWS AI offerings

Hands-on with AWS services

Creating your AWS account

Navigating through the AWS Management Console

Finding AWS services

Choosing the AWS region

Test driving the Amazon Rekognition service

Working with S3

Identity and Access Management

Getting familiar with the AWS CLI

Installing Python

Installing Python on macOS

Installing Python on Linux

Installing Python on Microsoft Windows

Windows 10

Earlier Windows versions

Installing the AWS CLI

Configuring the AWS CLI

Invoking the Rekognition service using the AWS CLI

Using Python for AI applications

Setting up a Python development environment

Setting up a Python virtual environment with Pipenv

Creating your first Python virtual environment

First project with the AWS SDK

Summary

References

Anatomy of a Modern AI Application

Technical requirements

Understanding the success factors of artificial intelligence applications

Understanding the architecture design principles for AI applications

Understanding the architecture of modern AI applications

Creation of custom AI capabilities

Working with a hands-on AI application architecture

Object detector architecture

Component interactions of the Object Detector

Creating the base project structure

Developing an AI application locally using AWS Chalice

Developing a demo application web user interface

Deploying AI application backends to AWS via Chalice

Deploying a static website via AWS S3

Summary

Further reading

Section 2: Building Applications with AWS AI Services

Detecting and Translating Text with Amazon Rekognition and Translate

Making the world smaller

Understanding the architecture of Pictorial Translator

Component interactions of Pictorial Translator

Setting up the project structure

Implementing services

Recognition service – text detection

Translation service – translating text

Storage service – uploading files

A recommendation on unit testing

Implementing RESTful endpoints

Translate the image text endpoint

Upload the image endpoint

Implementing the web user interface

index.html

scripts.js

Deploying Pictorial Translator to AWS

Discussing project enhancement ideas

Summary

Further reading

Performing Speech-to-Text and Vice Versa with Amazon Transcribe and Polly

Technical requirements

Technologies from science fiction

Understanding the architecture of Universal Translator

Component interactions of Universal Translator

Setting up the project structure

Implementing services

Transcription service – speech-to-text

Translation Service – translating text