fairlearn and AI_fairness
Fairlearn is an established, production-ready auditing and mitigation framework, while AI_Alameer appears to be an educational resource collection, making them complements where the latter could reference or build upon patterns from the former for learning purposes.
About fairlearn
fairlearn/fairlearn
A Python package to assess and improve fairness of machine learning models.
This tool helps AI system developers and data scientists evaluate and improve the fairness of their machine learning models. You provide an existing AI model and information about the groups you want to assess for fairness, and it outputs metrics quantifying potential biases and offers algorithms to mitigate unfairness. It's designed for anyone building AI systems for sensitive applications like hiring or lending.
About AI_fairness
Ali-Alameer/AI_fairness
This GitHub repository offers resources to create fair and unbiased AI systems, including libraries, tools and tutorials on identifying and mitigating bias in machine learning models and implementing fairness in AI.
Building AI systems that are fair and unbiased is critical for many organizations. This project provides libraries, tools, and tutorials to help you identify and reduce bias in your machine learning models, ensuring more equitable outcomes. It's designed for AI developers and researchers who are responsible for the ethical implementation of AI.
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