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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

Describe capabilities of AutoML

AutoML is a service that automates the process of applying machine learning to solve problems. It significantly reduces the complexity and time needed to produce a model by automating various steps of the machine learning process, including data preprocessing, feature selection, algorithm selection, and hyperparameter tuning.

With AutoML, users can quickly create high-quality machine learning models while maintaining full control and transparency. The service is designed to accommodate both novices and experts in machine learning. For beginners, it simplifies the process by abstracting away many of the complexities involved in building and tuning machine learning models. For experts, it provides a fast way to experiment with different models and parameters, saving time that can be used to focus on other aspects of their projects.

What’s preprocessing?

Preprocessing is the idea of preparing the data before actually using it in machine...

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