Fit interpretable models. Explain blackbox machine learning.
A curated list of awesome responsible machine learning resources.
moDel Agnostic Language for Exploration and eXplanation
Examples of techniques for training interpretable ML models, explaining ...
H2O.ai Machine Learning Interpretability Resources
📍 Interactive Studio for Explanatory Model Analysis
💡 Adversarial attacks on explanations and how to defend them
Model Agnostics breakDown plots
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learn...
A Julia package for interpretable machine learning with stochastic Shapl...
Break Down with interactions for local explanations (SHAP, BreakDown, iB...
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
An R package for computing asymmetric Shapley values to assess causality...
Interesting resources related to Explainable Artificial Intelligence, In...
Local Interpretable (Model-agnostic) Visual Explanations - model visuali...