interpretml / interpret
Fit interpretable models. Explain blackbox machine learning.
interpretml / interpret
truera / trulens
Evaluation and Tracking for LLM Experiments and AI Agents
MAIF / shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
microsoft / responsible-ai-toolbox
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.
csinva / imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
deel-ai / xplique
👋 Xplique is a Neural Networks Explainability Toolbox