Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539

Explain! Package with core wrappers for DrWhy universe.

tp1 IMP, ESI

tp2 IML ESI

examples for modelDown, package that turns model into HTML pages

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

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

Implementation of the Anchors algorithm: Explain black-box ML models

Micro-reserve model using XGBoost

An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model

Show case for modelStudio based on ⚽⚽⚽FIFA 20 ⚽⚽⚽

Variable importance via oscillations

Data generator for Arena - interactive XAI dashboard

H2O.ai Machine Learning Interpretability Resources

A java project made in january as an Upgrad assignment using servlet-jsp

XAI Stories 2.0. eXplainable Artificial Intelligence for Retail Analytics - case studies

XMLX GitHub configuration

High precision anchor black box explanation algorithm

Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.

GitHub repository of the Introduction to Machine Learning course in the Hebrew University of Jerusalem. Includes code examples, labs, and exercise templates