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Microsoft Azure AI Fundamentals AI-900 Exam Guide

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

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781835885666
Length 288 pages
Edition 1st Edition
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Authors (2):
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Steve Miles Steve Miles
Author Profile Icon Steve Miles
Steve Miles
Aaron Guilmette Aaron Guilmette
Author Profile Icon Aaron Guilmette
Aaron Guilmette
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Table of Contents (20) Chapters Close

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 19. Other Books You May Enjoy

Identify common scenarios for generative AI

Generative AI, with its ability to create new content, has applications spanning numerous fields. Here are some common scenarios where generative AI is making a significant impact, along with examples for each.

Image generation

Multimodal generative AI can create new images from textual descriptions, such as generating photorealistic images of objects or scenes that don’t exist, using models such as OpenAI’s DALL-E or Midjourney:

Figure 10.2 – Generating an image with GPT4

Figure 10.2 – Generating an image with GPT4

Text generation

Generative AI can be used to produce coherent and contextually relevant text for articles or stories by utilizing models such as GPT-3 from OpenAI:

Figure 10.3 – Text generation using GPT-3.5

Figure 10.3 – Text generation using GPT-3.5

Music creation

Generative AI can compose new music pieces or songs in various genres by learning from a vast dataset of music, exemplified by projects such as OpenAI...

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