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A game theoretic approach to explain the output of any machine learning model.
Fit interpretable models. Explain blackbox machine learning.
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Interactive architecture diagrams for codebases
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
XAI - An eXplainability toolbox for machine learning