Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

Home for explainer documents originated by the Microsoft Edge team

Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world datasets and workflows.

A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.

Make sense of any code, anytime. 🚀

Explanation method for Graph Neural Networks (GNNs)

ImputeGAP: A library of Imputation Techniques for Time Series Data

Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022

An interactive exploration of various number formats

SudokuExplainer (SE)

An explainer and diagram to help understand the syntax of the arc command of SVG paths.

Different approaches to solving coding challenges, along with explanations of the thinking involved.

Explains Tor Consensus with a visualization and explaination

PGExplainer is a Minimal SudokuExplainer, to rate (ER/EP/ED) sudoku puzzles.

Intuitive Zero-Knowledge Primer.

A LIME explainer app for fine-grained sentiment classification, written using Streamlit.

Application for explaining difficult to understand textbooks based on Yandex Cloud API (YandexGPT-Pro, Yandex-OCR)

A small explainer repository that shows how to use the BEM syntax in CSS.

Implementation of Model-Agnostic Graph Explainability Technique from Scratch in PyTorch