Popular GitHub Repositories for Iml

Fit interpretable models. Explain blackbox machine learning.

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

H2O.ai Machine Learning Interpretability Resources

? Interactive Studio for Explanatory Model Analysis

? Adversarial attacks on explanations and how to defend them

An interactive framework to visualize and analyze your AutoML process in real-time.

Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN

Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/

Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.

Article for Special Edition of Information: Machine Learning with Python

Repository for the code of the "Introduction to Machine Learning" (IML) lecture at the "Learning & Adaptive Systems Group" at ETH Zurich.