XAI - An eXplainability toolbox for machine learning

This repository contains demo notebooks (sample code) for the AutoMLx (automated machine learning and explainability) package from Oracle Labs.

Open source software for machine learning production monitoring : maintain control over production models, detect bias, explain your results.

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

Kaggle Courses - All Exercises of the respective courses.

Notebook examples from "A Practical Overview of Interpretable Machine Learning" blog post.

This repository contains all the pre-requisite notebooks for my internship as a Machine Learning Developer at Technocolabs. It includes some of the micro-courses from kaggle.

ConsisXAI is an implementation of a technique to evaluate global machine learning explainability (XAI) methods based on feature subset consistency

Sarcasm Classifier & ML Explainability tool

Using data to help us choice high quality wine

Análise de Intervenção em Ansiedade com Visualizações Estáticas e Insights

XMLX GitHub configuration

Using Deep Learning and other Machine Learning models to predict if someone has diabetes

Summarize "Interpretable Machine Learning" book.

XMLX GitHub configuration

This repository is a comprehensive collection of open-source tools, code implementations, research notes, and practical tutorials for Autonomous Driving technologies. Key focuses include AI/ML (Reinforcement Learning, Transformers, and Multimodal LLMs with PyTorch), Robotics (ROS integration and simulation), and Theoretical Foundations.

This project uses algorithms from Machine Learning Explainability to generate automated text explanations – Work in Progress