Microsoft Azure AI: A Beginner's Guide

Explore Azure Applied AI Services, Azure Cognitive Services and Azure Machine Learning with Practical Illustrations

Rekha Kodali, Sankara Narayanan Govindarajulu, Mohammed Athaulla

• Verlag: BPB Publications
• Jahr: 2022
• ISBN:
  9789355510518
• Thema: Ciencia de la computación
• Thema: Inteligencia artificial (IA) y semántica

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.

Table of Contents
1.Azure AI Platform and Services
2. Azure Computer Vision - Image Analysis, Processing, Content Moderation, Object and Face Detection
3. Computer Vision - Text Recognition, Optical Character Recognition, Spatial Analysis
4. Azure Cognitive Services - Custom Applications leveraging Decision, Language, Speech, Web Search
5. Azure Applied AI Services
6. Azure Applied AI Services -BOTs– A Brief Introduction
7. Machine Learning-Infusing ML in Custom Applications using ML.NET
8. Machine Learning - Using Azure ML Studio

CHAPTER 1

Azure AI Platform and Services

This chapter gives a basic introduction to the services/components provided by Azure to build AI based applications, Azure Cognitive Services, and Azure Computer Vision. It gives an overview of the available APIs and then gives an introduction to some sample use cases possible with Azure Computer Vision.

Structure

This chapter will cover the following topics:

• Platform provided by Azure to build AI-based applications
• Azure Cognitive Services – Core Aspects
• Conversational AI
• Azure Computer Vision
• Use Cases – Enterprise scenarios
• Setting up developer tools

Objective

After reading this chapter, the reader will be able to understand the Azure AI platform, the core concepts of Azure Cognitive Services, various services available within Azure Computer Vision, and specific use cases leveraging Azure Computer Vision.

Azure AI platform

Intelligent applications leverage Artificial Intelligence to deliver rich, adaptive, personalized, immersive, contextual experiences to users intelligently and are autonomous. Natural interfaces of text, speech, and vision unlocking new categories such as conversational commerce and AR/VR help in building immersive applications. Immersive applications incorporate intelligent features such as emotion and sentiment detection, vision and speech recognition, language understanding, knowledge, and search. Azure AI Platform provides the capability to build such applications very quickly. Azure AI Platform can be broadly classified into four Services/Components as depicted below:

Figure 1.1: Components provided by Azure to build AI-based applications

Azure Applied AI Services

Azure Applied AI Services are built leveraging Azure Cognitive Services. They help in tasks like boosting literacy in the classroom, diagnosing, monitoring anomalies in metrics, knowledge from mining documents, document understanding, transcription analysis, and more scenarios.

Figure 1.2: Azure Applied AI Services

• Azure Form Recognizer: It helps in identifying and extracting text, key/value pairs, and table data from form documents. It helps in ingesting text from forms and outputs structured data that includes the relationships in the original file.
• Azure Metrics Advisor: It helps in identifying and fixing problems leveraging a combination of near-real-time monitoring, adapting models to specific scenarios and helps with diagnostics and alerts.
• Azure Cognitive Search: It leverages built-in AI capabilities that help in identifying and exploring relevant content.
• Azure Immersive Reader: It is an inclusively designed tool that implements techniques to improve reading comprehension for language learners, new readers, and people with learning differences.
• Azure Video Analyser for Media: It helps extract metadata such as spoken words, faces etc from video and audio files.
• Azure Bot Service: It helps in developing conversational AI experiences.
• Azure Cognitive Services: Developers can rapidly consume high-level “finished” services that accelerate the development of AI solutions. They help in composing intelligent applications, customized to the organization’s availability, security, and compliance requirements.
• Azure Machine Learning: Consists of a set of comprehensive tools and frameworks that help build, deploy, and operationalize ML models. They provide an extensive set of supported tools and IDEs and Azure ML studio that help in easily building and fine-tuning ML models and deploying them.
• AI Infrastructure: AI Services and tools are backed by providing access to large scale infrastructure. It provides hyper-clusters of thousands of state-of-the-art GPUs, a breadth of AI hardware that includes the most comprehensive set of GPUs, and an array of general-purpose CPUs. It provides the latest high-bandwidth networks inside of every server.

We will look at some of the different types of applications that can be built using the Azure AI platform.

AI Services

AI services help access high-quality speech, vision, decision-making, language, and AI models through simple REST API calls and also provide the ability to create our own machine learning models.

AI services offered can be broadly classified as follows:

Figure 1.3: AI services

The following is an overview of AI Services:

Trained Services (Prebuilt)

Trained Services are Microsoft Azure Cognitive Services that offer a set of machine learning-based Azure Rest APIs that can be easily integrated into applications to infuse intelligence.

• Use cases for Trained/Prebuilt Services: The following are a few use cases for leveraging Cognitive/Trained services:

  

  Figure 1.4: Trained/Prebuilt/Cognitive Services
  • HealthCare: We can leverage OCR and Read APIs and other custom algorithms/logic as appropriate to go through large volumes of text that includes references to general entities (e.g. people’s names) and domain-specific ones (e.g. drug and disease names) that need to be connected and related. Sometimes we also need to combine this with imagery that’s analyzed in well-known ways (e.g. OCR) as well as apply leading-edge methods (e.g. AI-assisted diagnostics)
  • Oil and Gas companies: Oil and Gas companies have teams of geologists and other specialists that need to understand seismic and geologic data. They often have a huge library of PDFs with pictures of samples over sample sheets full of handwritten field notes. They need to connect places, people (domain experts), events, and navigate all this information to make key decisions. We can leverage OCR and other custom algorithms/logic to analyse and make decisions.
  • Insurance: Fraud Risk Analysis can be done by identifying anomalies in transactions using Azure Machine Learning, Face Recognition can be used as an additional authentication mechanism.

Conversational AI

Conversational AI helps in creating AI-based conversational interfaces. Azure provides Bot service which includes Bot Builder SDK and tools for end-to-end bot development and Bot Connector service to connect to multiple channels. We can create bots in a number of languages.

A Bot is a web service that communicates using a conversational interface and leverages Bot Framework Service to exchange events and messages between the Bot and the channel.

Bot functionality can be extended by adding additional features like NLP etc. Microsoft Cognitive Services such as Language Understanding Service (LUIS), can be added to the Bot interactions to make the conversation more intuitive.

The following are some ways of extending Bot functionality:

Figure 1.5: Extending Bot Functionality

The following table shows some of the additional features that can be leveraged to extend Bot functionality.

Feature	Description
Natural language processing	NLP can...