🐢 Open-Source Evaluation & Testing for LLMs and ML models
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Updated
May 27, 2024 - Python
🐢 Open-Source Evaluation & Testing for LLMs and ML models
Birhanu Eshete is an Associate Professor of Computer Science at the University of Michigan, Dearborn. His main research focus is in trustworthy machine learning with emphasis on security, safety, privacy, interpretability, fairness, and the dynamics thereof. He also studies online cybercrime and advanced and persistent threats (APTs).
Package for evaluating the performance of methods which aim to increase fairness, accountability and/or transparency
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Micro AI for multiple LLM switching, preparing datasets, training models, and deploying them in isolated environments using Docker
Ethical questions, risks and issues to think about to help create responsible AI products and services
Automate ethical AI assessments via GitHub Actions
This is the OFFICIAL CybernetiX S3C website.
The first ethical language generation model.
A bias bounty competition for income prediction. Using the pointer decision list method to improve group accuracy.
Credo AI Lens is a comprehensive assessment framework for AI systems. Lens standardizes model and data assessment, and acts as a central gateway to assessments created in the open source community.
A collection of awesome software, libraries, learning tutorials, documents, books & technical resources and cool stuff about dark web.
Welcome to the "Harnessing the Power of AI" workshop! This GitHub repository serves as a comprehensive resource for participants seeking hands-on learning and in-depth understanding of AI concepts, techniques, and tools.
Fair Statistical Learning Algorithms for Ethical Artificial Intelligence
Source code and models for the paper "Cyberbullying Detection with Fairness Constraints". IEEE Internet Computing, 2020
Personal Data Science Projects
Paper list and relevant material for Privacy-Preserving Computation.
Code for fair-representation learning path
A web app for ethical AI framework, internal evaluation workflow and monitoring production model
This project aims to understand the algorithmic bias in the corrections system through analyzing the COMPAS dataset.
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