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Index
Preface
About the Book
About the Authors
Objectives
Audience
Approach
Minimum Hardware Requirements
Software Requirements
Installation and Setup
Introduction to Amazon Web Services
Introduction
What is AWS?
What is Machine Learning?
What is Artificial Intelligence?
What is Amazon S3?
Why use S3?
The Basics of Working on AWS with S3
AWS Free-Tier Account
Importing and Exporting Data into S3
How S3 Differs from a Filesystem
Core S3 Concepts
S3 Operations
Data Replication
REST Interface
Exercise 1: Using the AWS Management Console to Create an S3 Bucket
Exercise 2: Importing and Exporting the File with your S3 Bucket
AWS Command-Line Interface (CLI)
Exercise 3: Configuring the Command-Line Interface
Command Line-Interface (CLI) Usage
Recursion and Parameters
Activity 1: Importing and Exporting the Data into S3 with the CLI
Using the AWS Console to Identify Machine Learning Services
Exercise 4: Navigating the AWS Management Console
Activity 2: Testing the Amazon Comprehend's API Features
Summary
Summarizing Text Documents Using NLP
Introduction
What is Natural Language Processing?
Using Amazon Comprehend to Inspect Text and Determine the Primary Language
Exercise 5: Detecting the Dominant Language Using the Command-Line Interface in a text document
Exercise 6: Detecting the Dominant Language in Multiple Documents by Using the Command-Line Interface (CLI)
Extracting Information in a Set of Documents
Detecting Named Entities – AWS SDK for Python (boto3)
DetectEntites – Input and Output
Exercise 7: Determining the Named Entities in a Document
DetectEntities in a Set of Documents (Text Files)
Detecting Key Phrases
Exercise 8: Determining the Key Phrase Detection.
Detecting Sentiments
Exercise 9: Detecting Sentiment Analysis
Setting up a Lambda function and Analyzing Imported Text Using Comprehend
What is AWS Lambda?
What does AWS Lambda do?
Lambda Function Anatomy
Exercise 10: Setting up a Lambda function for S3
Exercise 11: Configuring the Trigger for an S3 Bucket
Exercise 12: Assigning Policies to S3_trigger to Access Comprehend
Activity 3: Integrating Lambda with Amazon Comprehend to Perform Text Analysis
Summary
Perform Topic Modeling and Theme Extraction
Introduction
Extracting and Analyzing Common Themes
Topic Modeling with Latent Dirichlet Allocation (LDA)
Basic LDA example
Why Use LDA?
Amazon Comprehend–Topic Modeling Guidelines
Exercise 13: Topic Modeling of a Known Topic Structure
Exercise 14: Performing Known Structure Analysis
Activity 4: Perform Topic Modeling on a Set of Documents with Unknown Topics
Summary
Creating a Chatbot with Natural Language
Introduction
What is a Chatbot?
The Business Case for Chatbots
What is Natural Language Understanding?
Core Concepts in a Nutshell
Setting Up with Amazon Lex
Introduction
Exercise 15: Creating a Sample Chatbot to Order Flowers
Creating a Custom Chatbot
A Bot Recognizing an Intent and Filling a Slot
Exercise 16: Creating a Bot that will Recognize an Intent and Fill a Slot
Natural Language Understanding Engine
Lambda Function – Implementation of Business Logic
Exercise 17: Creating a Lambda Function to Handle Chatbot Fulfillment
Implementing the Lambda Function
Input Parameter Structure
Implementing the High-Level Handler Function
Implementing the Function to Retrieve the Market Quote
Returning the Information to the Calling App (The Chatbot)
Connecting to the Chatbot
Activity 5: Creating a Custom Bot and Configuring the Bot
Summary
Using Speech with the Chatbot
Introduction
Amazon Connect Basics
Free Tier Information
Interacting with the Chatbot
Talking to Your Chatbot through a Call Center using Amazon Connect
Exercise 18: Creating a Personal Call Center
Exercise 19: Obtaining a Free Phone Number for your Call Center
Using Amazon Lex Chatbots with Amazon Connect
Understanding Contact Flows
Contact Flow Templates
Exercise 20: Connect the Call Center to Your Lex Chatbot
Activity 1: Creating a Custom Bot and Connecting the Bot with Amazon Connect
Summary
Analyzing Images with Computer Vision
Introduction
Amazon Rekognition Basics
Free Tier Information on Amazon Rekognition
Rekognition and Deep Learning
Detect Objects and Scenes in Images
Exercise 21: Detecting Objects and Scenes using your own images
Image Moderation
Exercise 22: Detecting objectionable content in images
Facial Analysis
Exercise 23: Analyzing Faces in your Own Images
Celebrity Recognition
Exercise 24: Recognizing Celebrities in your Own Images
Face Comparison
Activity 1: Creating and Analyzing Different Faces in Rekognition
Text in Images
Exercise 25: Extracting Text from your Own Images
Summary
Appendix A
Chapter 1: Introduction to Amazon Web Services
Activity 1: Importing and exporting the data into S3 with the CLI.
Activity 2: Test Amazon Comprehends API features.
Chapter 2: Summarizing Text Documents Using NLP
Activity 3: Integrating Lambda with Amazon Comprehend to perform text analysis
Chapter 3: Perform Topic Modeling and Theme Extraction
Activity 4: Perform Topic modeling on a set of documents with unknown topics
Chapter 4: Creating a Chatbot with Natural Language
Activity 5: Creating a custom bot and configure the bot
Chapter 5: Using Speech with the Chatbot
Activity 6: Creating a custom bot and connect the bot with Amazon Connect
Chapter 6: Analyzing Images with Computer Vision
Activity 7: Compare faces in your own images
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