Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications

TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!

Local explanations with uncertainty 💐!

The Machine Learning Toybox for testing the behavior of autonomous agents.

For <Does It Make Sense? And Why? A Pilot Study for Sense Making and Explanation>. Accepted by ACL2019

Local Interpretable Model-Agnostic Explanations For Time Series Forecast Models

explainy is a Python library for generating machine learning model explanations for humans

This repository will be really helpful, if you want to learn from the scratch in Python Programming Languages. Also, makes your strong in Basic Python.

This is the official PyTorch implementation of our NeurIPS 2021 paper: "SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning"

Causality-Aware Local Interpretable Model Agnostic Explanations

Detailed Explanation of Stock Price Prediction using Linear Regression

ELIH: Explain Machine Learning predictions like I'm a human

This is a python application for an explanation of Contract Testing based on Pact.

[LREC2022] SuMe: A Dataset towards Summarizing biomedical Mechanisms

A developing review-awared recommender system with pytorch

A repository for a chess app in Python (Assignment 13). Give me 1 ⭐ if it’s cool.

The repository contains all the Playbooks and other files used to work with different applications for Ansible

The purpose of this repository is to demonstrate how to use NLP explanation/interpretability tools.

This project lets you learn who to implement a linear regression to predict the price of a car based on its mileage. (based on the 42 school subject)

FSK algorithm for Assignment with one sound application