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Machine Learning Security with Azure

You're reading from Machine Learning Security with Azure

Product type Book

Published in Dec 2023

Publisher Packt

ISBN-13 9781805120483

Pages 310 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Georgia Kalyva

Table of Contents (17) Chapters

Preface

1. Part 1: Planning for Azure Machine Learning Security

2. Chapter 1: Assessing the Vulnerability of Your Algorithms, Models, and AI Environments

3. Chapter 2: Understanding the Most Common Machine Learning Attacks

4. Chapter 3: Planning for Regulatory Compliance

5. Part 2: Securing Your Data

6. Chapter 4: Data Protection and Governance

7. Chapter 5: Data Privacy and Responsible AI Best Practices

8. Part 3: Securing and Monitoring Your AI Environment

9. Chapter 6: Managing and Securing Access

10. Chapter 7: Managing and Securing Your Azure Machine Learning Workspace

11. Chapter 8: Managing and Securing the MLOps Life Cycle

12. Chapter 9: Logging, Monitoring, and Threat Detection

13. Part 4: Best Practices for Enterprise Security in Azure Machine Learning

14. Chapter 10: Setting a Security Baseline for Your Azure Machine Learning Workloads

15. Index

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16. Other Books You May Enjoy

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Authors (1)

Georgia Kalyva

Georgia Kalyva is a technical trainer at Microsoft. She was recognized as a Microsoft AI MVP, is a Microsoft Certified Trainer, and is an international speaker with more than 10 years of experience in Microsoft Cloud, AI, and developer technologies. Her career covers several areas, ranging from designing and implementing solutions to business and digital transformation. She holds a bachelor's degree in informatics from the University of Piraeus, a master's degree in business administration from the University of Derby, and multiple Microsoft certifications. Georgia's honors include several awards from international technology and business competitions, and her journey to excellence stems from a growth mindset and a passion for technology.

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