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Microsoft Azure AI Fundamentals AI-900 Exam Guide
Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide : Gain proficiency in Azure AI and machine learning concepts and services to excel in the AI-900 exam

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Microsoft Azure AI Fundamentals AI-900 Exam Guide

Identify Features of Common AI Workloads

Welcome to the world of artificial intelligence (AI)!

When you think of AI, what comes to mind? If you’ve watched sci-fi movies, your mind might conjure images of walking and talking human-like androids from movies such as Blade Runner or Terminator. Or perhaps you think of just a voice, such as the HAL 9000 in 2001: A Space Odyssey or Tony Stark’s seemingly all-knowing computational butler, Jarvis, as featured in Iron Man.

While that future is still a ways off, there are some pretty amazing things that AI can do right now. Artificial intelligence is software technology that imitates certain human capabilities, such as interpreting images and language or predicting outcomes of scenarios based on historical data and patterns.

In this book, you’ll learn about the broad range of AI technologies and capabilities that are available inside the Microsoft Azure platform. And, throughout this book, you’ll be exposed...

1 Identify Features of Common AI Workloads

Welcome to the world of artificial intelligence (AI)!

When you think of AI, what comes to mind? If you’ve watched sci-fi movies, your mind might conjure images of walking and talking human-like androids from movies like Blade Runner or Terminator. Or perhaps you think of just a voice like the HAL 9000 in 2001: A Space Odyssey or Tony Stark’s seemingly all-knowing computational butler, Jarvis, as featured in Iron Man.

While that future is still a ways off, there are some pretty amazing things that AI can do right now. Artificial intelligence is software technology that imitates certain human capabilities, such as interpreting images and language or predicting outcomes of scenarios based on historical data and patterns.

In this book, you’ll learn about the broad range of AI technologies and capabilities that are available inside the Microsoft Azure platform.

The objectives and skills we’ll cover in this chapter include...

Identify features of data monitoring and anomaly detection workloads

Anomaly Detector is an AI service equipped with a suite of APIs designed to empower users in monitoring and identifying anomalies within their time series data, even with limited Machine Learning (ML) expertise. Whether you require batch validation or real-time inference, Anomaly Detector has you covered.

This service offers two primary functionalities:

  • Univariate Anomaly Detection
  • Multivariate Anomaly Detection

Univariate Anomaly Detection allows users to identify anomalies in a single variable, such as revenue or cost, without the need for extensive ML knowledge. The model selection process is automated based on the data pattern, ensuring optimal performance regardless of industry, scenario, or data volume. By leveraging time series data, the API establishes boundaries for anomaly detection, determines expected values, and identifies anomalous data points.

On the other hand, Multivariate Anomaly Detection APIs enable...

Identify computer vision workloads

Azure's Azure AI Vision (also referred to as computer vision) service offers access to cutting-edge algorithms designed to process images and provide relevant information based on specific visual features.

The service boasts several key functionalities:

  • Optical Character Recognition (OCR): This feature enables the extraction of text from images, including both printed and handwritten text from various sources such as photos and documents. Utilizing deep-learning-based models, the OCR service works across different surfaces and backgrounds, including business documents, invoices, receipts, posters, business cards, letters, and whiteboards. Additionally, it supports multiple languages for extracting printed text.
  • Image Analysis: The Image Analysis service extracts a wide range of visual features from images, including objects, faces, adult content, and automatically generated text descriptions.
  • Face Recognition: The Face service provides AI algorithms...

Identify natural language processing workloads

Natural language processing (NLP) is a branch of AI focused on comprehending and responding to human language. The goal of NLP is to allow computers to interpret text similarly to humans and provide realistic dialogue and responses. Several popular and common consumer AI-based services, such as OpenAI’s ChatGPT or predictive text on a smartphone, use natural language processing to help understand input and context.

NLP is a building block for many other AI services, such as text analytics, which extract information from unstructured text. Examples of NLP applications include sentiment analysis for product marketing campaigns on social media, document summarization in a catalog search application, and extracting brands and company names from text.

Azure AI Language, a cloud-based service, offers tools for understanding and analyzing text. It features sentiment analysis, key phrase identification, text summarization, and conversational...

Identify knowledge mining workloads

You can think of knowledge mining a bit like an AI-powered search engine. Traditional search engines easily catalog and index traditional text pages. However, they may be less capable of ingesting unstructured data such as directories of documents, spreadsheets, presentations, and images and answering search queries for it.

Azure AI Knowledge Mining is a comprehensive suite of tools and services designed to extract valuable insights and knowledge from large volumes of unstructured data, such as documents, images, videos, and audio files. This suite leverages advanced artificial intelligence technologies, including natural language processing, computer vision, and machine learning, to enable organizations to understand their volumes of data.

Let’s look at the key feature of Azure AI Knowledge Mining:

  • Powerful text analytics capabilities: Using state-of-the-art NLP algorithms, organizations can extract entities, key phrases, and sentiment from...

Identify document intelligence workloads

Azure AI Document Intelligence (formerly known as Azure Form Recognizer) is a set of capabilities that allows automation to make decisions based on extracted text.

For example, it might be very easy for a human to look at a receipt or an invoice and determine what it is, what the different data fields mean (such as a subtotal or an address) and insert them accordingly into a database or perform some other activity with them. This type of business process automation is very difficult for traditional computer systems to do. AI-enabled document intelligence can be used to bridge that gap to identify certain types of data and map them to appropriate fields.

Azure AI Document Intelligence is a comprehensive suite of tools and services designed to streamline document processing tasks using advanced artificial intelligence technologies. This service enables organizations to extract valuable insights from various types of documents, including scanned images...

Identify features of generative AI workloads

If you’ve been paying attention to the media over the last year or so, you’ve probably seen some examples of generative AI tools like ChatGPT, Bing Image Creator, and Midjourney. Each of these types of tools are able to generate new content (hence the term generative AI) as the result of a natural language instructive input, also known as a prompt.

Azure AI Generative AI is a set of tools and services within the Azure AI ecosystem designed to enable the creation of new content, such as images, text, audio, and video, based on existing data patterns. This cutting-edge technology leverages deep learning techniques to mimic human creativity and generate content that is realistic and relevant to specific use cases.

Azure AI Generative AI can be used to generate high-quality images. Using Generative Adversarial Networks (GANs) and other advanced techniques, Azure AI can create realistic images that closely resemble those found in real...

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Key benefits

  • Discover Azure AI services, including computer vision, Auto ML, NLP, and OpenAI
  • Explore AI use cases, such as image identification, chatbots, and more
  • Work through 145 practice questions under chapter-end self-assessments and mock exams
  • Purchase of this book unlocks access to web-based exam prep resources, including mock exams, flashcards, and exam tips

Description

The AI-900 exam helps you take your first step into an AI-shaped future. Regardless of your technical background, this book will help you test your understanding of the key AI-related topics and tools used to develop AI solutions in Azure cloud. This exam guide focuses on AI workloads, including natural language processing (NLP) and large language models (LLMs). You’ll explore Microsoft’s responsible AI principles like safety and accountability. Then, you’ll cover the basics of machine learning (ML), including classification and deep learning, and learn how to use training and validation datasets with Azure ML. Using Azure AI Vision, face detection, and Video Indexer services, you’ll get up to speed with computer vision-related topics like image classification, object detection, and facial detection. Later chapters cover NLP features such as key phrase extraction, sentiment analysis, and speech processing using Azure AI Language, speech, and translator services. The book also guides you through identifying GenAI models and leveraging Azure OpenAI Service for content generation. At the end of each chapter, you’ll find chapter review questions with answers, provided as an online resource. By the end of this exam guide, you’ll be able to work with AI solutions in Azure and pass the AI-900 exam using the online exam prep resources.

Who is this book for?

Whether you're a cloud engineer, software developer, an aspiring data scientist, or simply interested in learning AI/ML concepts and capabilities on Azure, this book is for you. The book also serves as a foundation for those looking to attempt more advanced AI and data science-related certification exams (e.g. Microsoft Certified: Azure AI Engineer Associate). Although no experience in data science and software engineering is required, basic knowledge of cloud concepts and client-server applications is assumed.

What you will learn

  • Discover various types of artificial intelligence (AI)workloads and services in Azure
  • Cover Microsoft's guiding principles for responsible AI development and use
  • Understand the fundamental principles of how AI and machine learning work
  • Explore how AI models can recognize content in images and documents
  • Gain insights into the features and use cases for natural language processing
  • Explore the capabilities of generative AI services

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Length: 288 pages
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Language : English
ISBN-13 : 9781835885666
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Table of Contents

19 Chapters
Part 1: Identify Features of Common AI Workloads Chevron down icon Chevron up icon
Chapter 1: Identify Features of Common AI Workloads Chevron down icon Chevron up icon
Chapter 2: Identify the Guiding Principles for Responsible AI Chevron down icon Chevron up icon
Part 2: Describe the Fundamental Principles of Machine Learning on Azure Chevron down icon Chevron up icon
Chapter 3: Identify Common Machine Learning Techniques Chevron down icon Chevron up icon
Chapter 4: Describe Core Machine Learning Concepts Chevron down icon Chevron up icon
Chapter 5: Describe Azure Machine Learning Capabilities Chevron down icon Chevron up icon
Part 3: Describe Features of Computer Vision Workloads on Azure Chevron down icon Chevron up icon
Chapter 6: Identify Common Types of Computer Vision Solutions Chevron down icon Chevron up icon
Chapter 7: Identify Azure Tools and Services for Computer Vision Tasks Chevron down icon Chevron up icon
Part 4: Describe Features of Natural Language Processing (NLP) Workloads on Azure Chevron down icon Chevron up icon
Chapter 8: Identify Features of Common NLP Workload Scenarios Chevron down icon Chevron up icon
Chapter 9: Identify Azure Tools and Services for NLP Workloads Chevron down icon Chevron up icon
Part 5: Describe Features of Generative AI Workloads on Azure Chevron down icon Chevron up icon
Chapter 10: Identify Features of Generative AI Solutions Chevron down icon Chevron up icon
Chapter 11: Identify Capabilities of Azure OpenAI Service Chevron down icon Chevron up icon
Chapter 12: Accessing the Online Practice Resources Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

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Microsoft Azure AI Fundamentals AI-900 Exam Guide was one of the most valuable resources used for exam preparations.
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