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AI Bias Detection and Mitigation

AI systems can unintentionally reinforce harmful bias. This course will teach you how to detect, analyze, and mitigate bias in machine learning models using real-world tools and techniques

Ed Freitas - Pluralsight course - AI Bias Detection and Mitigation
by Ed Freitas

What you'll learn

AI models can unintentionally produce biased outcomes that negatively impact individuals and organizations. In this course, AI Bias Detection and Mitigation, you’ll learn to identify, analyze, and reduce bias in machine learning systems. First, you’ll explore the core concepts of AI bias, including its types, sources, and real-world consequences. Next, you’ll discover how to detect bias using tools like Fairlearn and perform dataset analysis to uncover imbalance. Finally, you’ll learn how to apply bias mitigation strategies such as preprocessing, in-processing, and postprocessing techniques. When you’re finished with this course, you’ll have the skills and knowledge of responsible AI development needed to build fairer, more trustworthy models

Table of contents

About the author

Ed Freitas - Pluralsight course - AI Bias Detection and Mitigation
Ed Freitas

Eduardo is a technology enthusiast, software architect and customer success advocate. He's designed enterprise .NET solutions that extract, validate and automate critical business processes such as Accounts Payable and Mailroom solutions. He's a well-known specialist in the Enterprise Content Management market segment, specifically focusing on data capture & extraction and document process automation.

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