trustyai-explainability/trustyai-explainability

Interpretability and explainability of data and machine learning models

Human-explainable AI.

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

A Python package to assess and improve fairness of machine learning models.

A game theoretic approach to explain the output of any machine learning model.

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.

This is an open-source tool to assess and improve the trustworthiness of AI systems.

Deep Insight And Neural Network Analysis

A series of XAI and causal discovery algorithm projects