the APPLIED AI AND NATURAL LANGUAGE PROCESSING WORKSHOP - : learn how to use powerful natural... language processing techniques within your own art.

✍ Scribed by KRISHNA JACKOVICH JEFFREY RICHARDS RUZE SANKAR

• Publisher: PACKT PUBLISHING LIMITED
• Year: 2020
• Tongue: English
• Leaves: 383
• Category: Library

✦ Table of Contents

Cover
FM
Copyright
Table of Contents
Preface
Chapter 1: An Introduction to AWS
Introduction
How Is AWS Special?
What Is ML?
What Is AI?
What Is Amazon S3?
Why Use S3?
The Basics of Working on AWS with S3
AWS Free-Tier Account
AWS Account Setup and Navigation
Downloading the Support Materials for This Book
A Word about Jupyter Notebooks
Importing and Exporting Data into S3
How S3 Differs from a Filesystem
Core S3 Concepts
S3 Operations
Data Replication
The REST Interface
Exercise 1.01: Using the AWS Management Console to Create an S3 Bucket
Exercise 1.02: Importing and Exporting the File with Your S3 Bucket
The AWS CLI
Exercise 1.03: Configuring the CLI
CLI Usage
Recursion and Parameters
Activity 1.01: Putting the Data into S3 with the CLI
Using the AWS Console to Identify ML Services
Exercise 1.04: Navigating the AWS Management Console
Exercise 1.05: Testing the Amazon Comprehend API Features
The Utility of the AWS Console Interface to AI Services
Summary
Chapter 2: Analyzing Documents and Text with Natural Language Processing
Introduction
Serverless Computing
Amazon Lambda and Function as a Service
Serverless Computing as an Approach
Amazon Comprehend
What Is an NLP Service?
Using Amazon Comprehend to Inspect Text and Determine the Primary Language
Exercise 2.01: Detecting the Dominant Language in a Text Document Using the Command-Line Interface
Exercise 2.02: Detecting the Dominant Language in Multiple Documents by Using the CLI
Extracting Information from a Set of Documents
Detecting Named Entities—AWS SDK for Python (boto3)
DetectEntities – Input and Output
Exercise 2.03: Determining the Named Entities in a Document (the DetectEntities method)
Exercise 2.04: Detecting Entities in a Set of Documents (Text Files)
Detecting Key Phrases
Exercise 2.05: Detecting Key Phrases
Detecting Sentiments
Exercise 2.06: Conducting Sentiment Analysis
Setting Up a Lambda Function and Analyzing Imported Text Using Comprehend
Integrating Comprehend and AWS Lambda for responsive NLP
What Is AWS Lambda?
What Does AWS Lambda Do?
Lambda Function Anatomy
Exercise 2.07: Setting Up a Lambda Function for S3
Exercise 2.08: Assigning Policies to S3_trigger to Access Comprehend
Activity 2.01: Integrating Lambda with Amazon Comprehend to Perform Text Analysis
Amazon Textract
Exercise 2.09: Extracting Tax Information Using Amazon Textract
Summary
Chapter 3: Topic Modeling and Theme Extraction
Introduction
Topic Modeling with Latent Dirichlet Allocation (LDA)
Basic LDA Example
Why Use LDA?
Amazon Comprehend—Topic Modeling Guidelines
Exercise 3.01: Using Amazon Comprehend to Perform Topic Modeling on Two Documents with Known Topics
Exercise 3.02: Performing Known Structure Analysis Programmatically
Activity 3.01: Performing Topic Modeling on a Set of Documents with Unknown Topics
Summary
Chapter 4: Conversational Artificial Intelligence
Introduction to Conversational AI
Interaction Types
Omnichannel
What Is a Chatbot?
What Is Natural Language Understanding?
Core Concepts in a Nutshell
Chatbot
Utterances
Intent
Prompts
Slot
Fulfillment
Best Practices for Designing Conversational AI
Creating a Custom Chatbot
A Bot That Recognizes an Intent and Filling a Slot
Exercise 4.01: Creating a Bot That Will Recognize an Intent and Fill a Slot
Natural Language Understanding Engine
Lambda Function – Implementing Business Logic
Exercise 4.02: 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
Debugging Tips
Summary
Chapter 5: Using Speech with the Chatbot
Amazon Connect Basics
Free Tier Information
Interacting with the Chatbot
Talking to Your Chatbot through a Call Center Using Amazon Connect
Exercise 5.01: Creating a Personal Call Center
Exercise 5.02: Obtaining a Free Phone Number for Your Call Center
Using Amazon Lex Chatbots with Amazon Connect
Understanding Contact Flows
Contact Flow Templates
Exercise 5.03: Connecting the Call Center to Your Lex Chatbot
Activity 5.01: Creating a Custom Bot and Connecting the Bot with Amazon Connect
Summary
Chapter 6: Computer Vision and Image Processing
Introduction
Amazon Rekognition Basics
Free Tier Information on Amazon Rekognition
Rekognition and Deep Learning
Detecting Objects and Scenes in Images
Exercise 6.01: Detecting Objects and Scenes Using Your Images
Image Moderation
Exercise 6.02: Detecting Objectionable Content in Images
Facial Analysis
Exercise 6.03: Analyzing Faces with Your Own Images
Celebrity Recognition
Exercise 6.04: Recognizing Celebrities in Your Images
Face Comparison
Activity 6.01: Creating and Analyzing Different Faces in Rekognition
Text in Images
Exercise 6.05: Extracting Text from Your Own Images
Summary
Appendix
Index