Microsoft Azure AI: A Beginner’s Guide: Explore Azure Applied AI Services, Azure Cognitive Services and Azure Machine Learning with Practical Illustrations

Length: 256 pages
Edition: 1
Language: English
Publisher: BPB Publications
Publication Date: 2022-04-21
ISBN-10: 9355510519
ISBN-13: 9789355510518
Sales Rank: #3306643 (See Top 100 Books)

Explore Azure AI Platform.

Key Features

Easy-to-follow tutorial for getting started with the Azure AI platform.
Integrated platform for developing, deploying, and managing AI apps.
Includes real-world scenarios and use-cases to fully explore Azure AI Platform.

Description

Microsoft Azure AI A Beginner’s Guide explains the fundamentals of Azure AI and some more advanced topics. The sole objective of the book is to provide hands-on experience working with the various services, APIs, and tools available in the Azure AI Platform. This book begins by discussing the fundamentals of the Azure AI platform and the essential principles behind the Azure AI ecosystem and services. Readers will become familiar with the essential services, use cases, and examples provided by Azure AI Platform and Services, including Azure Cognitive Services, Azure Computer Vision, Azure Applied AI Services, and Azure Machine Learning.

The author focuses on teaching how to utilize Azure Cognitive services to construct intelligent apps, including Image Processing, Object Detection, Text Recognition, OCR, Spatial Analysis, and Face Recognition using Computer Vision. Readers can investigate Azure Applied AI Services, including Form Recognizer, Metrics Advisor, Cognitive Search, Immersive Reader, Video Analyzer, and Azure Bot Service. Bot Framework and the Bot Framework Emulator will be explored in further detail, and how they can be used in AI applications to improve their conversational user interfaces. With Azure Machine Learning Studio, you will also learn to incorporate machine learning into your enterprise-level applications.

What you will learn

Get familiar with Azure AI Platform and the cognitive capabilities of Azure.
Learn to create apps that can process photos, detect faces, and detect objects.
Utilize OCR, handwriting recognition, and spatial analysis in your development.
Learn about Azure AI services like Form Recognizer, Metrics Advisor, Cognitive Search, Azure Immersive Reader, and Video Analyzer.
Try out several NLP applications with the Azure BOT framework.

Who this book is for

This book teaches AI developers, machine learning engineers, .NET developers, and architects how to swiftly develop intelligent applications utilizing the Azure AI Platform. Knowledge of.NET or.NET Core is strongly advised to get the most out of the book.

Cover Page
Title Page
Copyright Page
Foreword
Dedication Page
About the Authors
About the Reviewer
Acknowledgements
Preface
Errata
Table of Contents
1. Azure AI Platform and Services
    Structure
    Objective
    Azure AI platform
        Azure Applied AI Services
    AI Services
        Trained Services (Prebuilt) 
    Conversational AI 
    Custom services
    Azure Cognitive Services
    Azure Vision Service
    Accessing the APIs
    Use cases
    Setting up Developer Tools
    Conclusion
    Multiple choice questions
        Answerss
2. Azure Computer Vision - Image Analysis, Processing, Object Detection
    Structure
    Objective
    Image processing
    Image analytics - Azure Computer Vision API
    Image Analytics -Lab
    Image Classification using Azure Custom Vision Service
        Azure Custom Vision Service-Image Classification Lab
    Object detection using Azure Custom Vision Service
    Conclusion
    Multiple choice questions
        Answers
3. Computer Vision - Optical Character Recognition, Face API, and Spatial Analysis
    Structure
    Objective
    Handwritten / Printed text recognition
    Handwriting recognition lab
    Face recognition
    Computer Vision - Face API - In Detail
    Computer Vision - Face API Lab
    Spatial Analysis
    Sample use cases
    Conclusion
    Multiple choice questions
    Questions
        Answers
4. Azure Cognitive Services
    Structure
    Objective
    Decision service
        Content Moderator-Use case
        Content Moderator-Detailed APIs
    Personalizer
    Language Service
    Azure Logic Apps and Functions
    Lab - Create Logic App using OCR and Text Analytics and Azure Functions 
    Speech
    Bing Web Search
        Lab
    Azure Cognitive Services containers
    Conclusion
    Multiple Choice Questions
    Questions
        Answers
5. Azure Applied AI Services
    Structure
    Objective
    Overview of Azure Applied AI Services
    Azure Metrics Advisor
    Azure Immersive Reader
    Azure Video Analyzer for Media
    Azure Form Recognizer
    Azure Cognitive Search
    Lab: Creating a Azure Cognitive Search Service
    Conclusion
    Multiple choice questions
        Answers
6. Bots - A Brief Introduction
    Structure
    Objective
    How Machines Learn – A Brief Introduction
    Introducing Bots
    The Bot Ecosystem
        The Bot Framework
        The Bot Framework Composer
        Cognitive Intelligence
            QnA Maker
            LUIS - Language Understanding Intelligent Service
            Azure Cognitive Services for Language 
        Search
        Storage
        Information sources
            Build Bots using the Bot Framework
    Lifecycle
    Reference Architecture
    The Bot Framework Emulator
        Building a Basic Bot
            Creating a QnA KB
            Using the Emulator
            Adding LUIS to the sample
            Adding a LUIS Model
            Adding a second QnA KB
            Creating a dispatch model using the Bot Framework Orchestrator
            Updating the BasicBot source code to include dispatch support
            Build and Test it using Emulator
            Adding the Oliver Garden FAQ as an exercise
            Enhancing it further
    Building the Bot Framework Composer
        Enterprise Scenarios
            A Customer scenario
        Typical use cases
    Conclusion
    Thought Experiment
7. Infusing ML in Custom Applications Using ML.NET
    Structure
    Objective
    Introducing ML.NET
        Algorithms supported by ML.NET
        Choosing the right algorithm
        Trainers
    Creating a ML.NET Model
        Samples
    Lab 1 - Creating Samples using ML.NET - Sentiment Analysis
    Lab 2 - Creating samples using ML.NET - Fare prediction
    Lab 3 - Creating samples using ML.NET - Issue classification
        ML.NET Model Builder
    Lab 4 - Creating sample using ML.NET Model Builder for sentiment analysis
    Conclusion
    Multiple choice questions
        Answers
8. Using Azure ML Studio
    Structure
    Objective
    Azure Machine Learning Studio
    Sample lab using Azure ML Studio using Automated machine learning UI no-code approach
    Sample Lab using Azure ML Studio Azure Machine Learning designer
    ML Ops
    Migration
    Azure ML library of algorithms
    Accord.NET -A brief Introduction
    Conclusion 
    Multiple choice questions
        Answers
Index