This repository contains course material, codes, and other components for the Azure ML Foundation Course Scholarship from Udacity.
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Updated
Jul 15, 2020
This repository contains course material, codes, and other components for the Azure ML Foundation Course Scholarship from Udacity.
Responsible AI tooling short list - a working list.
A collection of news articles, books, and papers on Responsible AI cases. The purpose is to study these cases and learn from them to avoid repeating the failures of the past.
Code for paper "Consequence-aware Sequential Counterfactual Generation" (https://link.springer.com/chapter/10.1007/978-3-030-86520-7_42), @ ECML PKDD 2021 (). Repository maintained by Philip Naumann.
This project is a set of tools to create a model card.
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training (ICML 2020)
Checklist for an analysis of various aspects of responsibility of models and data resources
Code for paper "XPROAX - Local explanations for text classification with progressive neighborhood approximation", DSAA 2021 (https://ieeexplore.ieee.org/abstract/document/9564153). Repository maintained by Yi Cai.
Official code of "Discover the Unknown Biased Attribute of an Image Classifier" (ICCV 2021)
FairWell is a Responsible AI tool developed using Streamlit
Responsible Prediction Making of COVID-19 Mortality (AAAI 2021)
Sample Selection for Fair and Robust Training (NeurIPS 2021)
Open-source toolkit to help companies implement responsible AI workflows.
ODSC East 2022 tutorial, workshop, and training prerequisites and resources will be available in this repository
Code for paper "A survey on datasets for fairness-aware learning", @ Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery (https://doi.org/10.1002/widm.1452). Repository maintained by Tai Le Quy.
"AdaFair: Cumulative Fairness Adaptive Boosting" algorithm (CIKM 2019) and its extension to other parity-based fairness notions (@Kais2022); Repository maintained by Vasileios Iosifidis.
A short Course Training Material by AI4D Lab on Machine Learning,Deep Learning and Responsible AI.
Official code of "StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis" (CVPR 2022)
Modern cloud-native federated data platform focused on data mesh paradigm while complying with state-of-the-art and conway's law.
Predict Student dropout using Responsible AI methodologies
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