fair-ml

There are 0 repository under fair-ml topic.

awesome-imbalanced-learning
ZhiningLiu1998 / awesome-imbalanced-learning
Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切：论文、代码、框架与库
awesome awesome-list imbalanced-learning imbalanced-classification class-imbalance machine-learning ensemble-learning imbalanced-data deep-learning imbalanced-classes skewed-data fairness-ml fair-ml
1280
kozodoi / Fair_Credit_Scoring
Fair ML in credit scoring: Assessment, implementation and profit implications
fairness credit-scoring discrimination fair-ml benchmark
Language:Python 27
DataResponsibly / Virny
An in-depth performance profiling library for machine learning models
fair-ml machine-learning python responsible-ai robustness uncertainty-analysis
Language:Python 8
psunlpgroup / FairSumm
Code and Data for NAACL 2024 paper: Fair Abstractive Summarization of Diverse Perspectives
evaluation-metrics fair-ml fair-summarization large-language-models natural-language-processing summarization
Language:Jupyter Notebook 8
IBMDeveloperMEA / AI-Ethics
Fairness in data, and machine learning algorithms is critical to building safe and responsible AI systems from the ground up by design. Both technical and business AI stakeholders are in constant pursuit of fairness to ensure they meaningfully address problems like AI bias. While accuracy is one metric for evaluating the accuracy of a machine learning model, fairness gives us a way to understand the practical implications of deploying the model in a real-world situation.
ai-ethics ai-explainability ibm-cloud aif360 ai-fairness machine-learning explainable-ai fair-ml
3
aurorarq / euads-genderbias
Supporting material for the EuADS Summer School - A hands-on tutorial on explainable methods for machine learning with Python: applications to gender bias
explainable-ai fair-ml gender-bias machine-learning
Language:Jupyter Notebook 2
hcorinna / gradual-compatibility
:pencil: Exploring the gradual (in)compatibility of the fairness metrics independence, separation and sufficiency.
algorithmic-fairness fair-machine-learning fair-ml machine-learning python regularization reproducible-research
Language:Jupyter Notebook 2
DataResponsibly / MLcF
A controlled environment to play around with various data errors and stages in the ML lifecycle and measure their impact on model fairness and stability.
fair-ml fairness ml-lifecycle responsible-ai stability-ai
Language:Jupyter Notebook 1
hcorinna / utility-based-fairness
:pencil: Implementation of our approach for balancing the utility of the decision maker and the fairness towards the decision subjects for a prediction-based decision-making system
algorithmic-fairness fair-machine-learning fair-ml machine-learning pareto-front python reproducible-research
Language:Jupyter Notebook 1
nischaybikramthapa / predicting-hospital-los
Can we predict how long a patient will be in a hospital with a fair comparison on gender, race and health service areas?
adaboost-algorithm binaryclassification decision-trees fair-ml length-of-stay logistic-regression predictive-modeling random-forest
Language:Jupyter Notebook 1
birhanu-eshete / birhanu-eshete.github.io
Birhanu Eshete is an Assistant 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).
adversarial-machine-learning ethical-artificial-intelligence fair-ml privacy-preserving-machine-learning trustworthy-ai trustworthy-machine-learning transparent-ml
Language:HTML
pandorica-opens / Fair-Clustering
major ideas of the session "Fair Clustering" from the NeurIPS 2019 conference
fairness fair-clustering fair-ml clustering machine-learning
Language:Jupyter Notebook

fair-ml

ZhiningLiu1998 / awesome-imbalanced-learning

kozodoi / Fair_Credit_Scoring

DataResponsibly / Virny

psunlpgroup / FairSumm

IBMDeveloperMEA / AI-Ethics

aurorarq / euads-genderbias

hcorinna / gradual-compatibility

DataResponsibly / MLcF

hcorinna / utility-based-fairness

nischaybikramthapa / predicting-hospital-los

birhanu-eshete / birhanu-eshete.github.io

pandorica-opens / Fair-Clustering