You're reading from 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

Product type Paperback

Published in May 2024

Publisher Packt

ISBN-13 9781835885666

Length 288 pages

Edition 1st Edition

Languages

Python

Tools

Azure

Concepts

Artificial Intelligence

Authors (2):

Steve Miles

Aaron Guilmette

View More author details

Table of Contents (20) Chapters

Preface

1. Part 1: Identify Features of Common AI Workloads FREE CHAPTER

2. Chapter 1: Identify Features of Common AI Workloads

3. Chapter 2: Identify the Guiding Principles for Responsible AI

4. Part 2: Describe the Fundamental Principles of Machine Learning on Azure

5. Chapter 3: Identify Common Machine Learning Techniques

6. Chapter 4: Describe Core Machine Learning Concepts

7. Chapter 5: Describe Azure Machine Learning Capabilities

8. Part 3: Describe Features of Computer Vision Workloads on Azure

9. Chapter 6: Identify Common Types of Computer Vision Solutions

10. Chapter 7: Identify Azure Tools and Services for Computer Vision Tasks

11. Part 4: Describe Features of Natural Language Processing (NLP) Workloads on Azure

12. Chapter 8: Identify Features of Common NLP Workload Scenarios

13. Chapter 9: Identify Azure Tools and Services for NLP Workloads

14. Part 5: Describe Features of Generative AI Workloads on Azure

15. Chapter 10: Identify Features of Generative AI Solutions

16. Chapter 11: Identify Capabilities of Azure OpenAI Service

17. Chapter 12: Accessing the Online Practice Resources

18. Index

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Summary

This chapter provided complete coverage of the Describe features of computer vision workloads on Azure AI-900 Azure Fundamentals skills area.

In this chapter, you were introduced to the Azure AI Vision Studio tool and discovered the capabilities of the Azure AI Vision service regarding image classification, object detection, and OCR. You then learned about the Azure Face service, which can be used for facial detection, facial analysis, and recognition. Finally, we covered the Azure AI Video Indexer service, which can extract insights from video and audio files, as well as Microsoft’s positioning on responsible AI.

In the next chapter, you will learn how to describe the various features of natural language processing (NLP) workloads on Azure. NLP supports many of the popular commercial AI services available today.