jphall663/awesome-machine-learning-interpretability
A curated list of awesome responsible machine learning resources.
This project offers a curated collection of resources for anyone grappling with the ethical implications and responsible deployment of machine learning. It provides guidance, educational materials, and technical references to help you understand and address fairness, transparency, and accountability issues in AI systems. The primary users are professionals who work with or are impacted by AI, such as HR managers, legal experts, policymakers, and project managers, who need to navigate the complexities of AI ethics and governance.
3,996 stars. Actively maintained with 2 commits in the last 30 days.
Use this if you need to research or implement responsible machine learning practices, understand AI regulations, or educate yourself and your team on ethical AI development and deployment.
Not ideal if you are looking for a direct software tool to *build* machine learning models, as this is primarily a resource list, not a development library.
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CC0-1.0
Last pushed
Mar 11, 2026
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