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59 search results found

Datasets ⭐ 4,094

TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...

Awesome Machine Learning Interpretability ⭐ 3,241

A curated list of awesome responsible machine learning resources.

Aif360 ⭐ 2,293

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Fairlearn ⭐ 1,727

A Python package to assess and improve fairness of machine learning models.

Dalex ⭐ 1,242

moDel Agnostic Language for Exploration and eXplanation

Responsible Ai Toolbox ⭐ 1,187

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

Scikit Lego ⭐ 1,099

Extra blocks for scikit-learn pipelines.

Interpretable_machine_learning_with_python ⭐ 629

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Mli Resources ⭐ 405

H2O.ai Machine Learning Interpretability Resources

An experimental platform to quickly realize and compare with popular centralized federated learning algorithms. A realization of federated learning algorithm on fairness (FedFV, Federated Learning with Fair Averaging, https://fanxlxmu.github.io/publication/ijcai2021/) was accepted by IJCAI-21 (https://www.ijcai.org/proceedings/2021/223).

CMU Lecture: Machine Learning In Production / AI Engineering / Software Engineering for AI-Enabled Systems (SE4AI)

Nlp_newsletter ⭐ 264

📰Natural language processing (NLP) newsletter

Awesome Fairness In Ai ⭐ 257

A curated list of awesome Fairness in AI resources

Ml Fairness Gym ⭐ 246

Image Crop Analysis ⭐ 198

Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

Fair Classification ⭐ 144

Python code for training fair logistic regression classifiers.

The LinkedIn Fairness Toolkit (LiFT) is a Scala/Spark library that enables the measurement of fairness in large scale machine learning workflows.

Xaience ⭐ 100

All about explainable AI, algorithmic fairness and more

Fairness In Ml ⭐ 88

This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.

This is a collection of papers and other resources related to fairness.

Deep Explanation Penalization ⭐ 74

Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

Fairness_tutorial ⭐ 65

Hands-on tutorial on ML Fairness

Amazon Sagemaker Clarify ⭐ 63

Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models.

Fat Forensics ⭐ 63

Modular Python Toolbox for Fairness, Accountability and Transparency Forensics

Infairness ⭐ 58

PyTorch package to train and audit ML models for Individual Fairness

Awesome Distribution Shift ⭐ 57

A curated list of papers and resources about the distribution shift in machine learning.

Machine Learning Ethics References ⭐ 54

List of references about Machine Learning bias and ethics

A Python toolkit for analyzing machine learning models and datasets.

Responsibly ⭐ 41

Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰

Responsibleai ⭐ 34

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.

Awesome Ml Testing ⭐ 34

Awesome material(papers, tools, etc.) about testing machine learning system, including deep learning system.

Awesome Ml Fairness ⭐ 32

Papers and online resources related to machine learning fairness

MEDFAIR: Benchmarking Fairness for Medical Imaging

Guardian Ai ⭐ 29

Oracle Guardian AI Open Source Project is a library consisting of tools to assess fairness/bias and privacy of machine learning models and data sets.

Fairness.jl ⭐ 28

Julia Toolkit with fairness metrics and bias mitigation algorithms

Fairness ⭐ 27

R package for computing and visualizing fair ML metrics

Fair Ml Reading Group ⭐ 25

Reading history for Fair ML Reading Group in Melbourne

Package for evaluating the performance of methods which aim to increase fairness, accountability and/or transparency

Equalityml ⭐ 24

Evidence-based tools and community collaboration to end algorithmic bias, one data scientist at a time.

Multi-Calibration & Multi-Accuracy Boosting for R

Fairmlhealth ⭐ 20

Healthcare-specific tools for bias analysis

Ensure Loan Fairness Aif360 ⭐ 19

A demonstration of the AI Fairness 360 toolbox for bias metrics, explanations, and remediation. Code Pattern: https://developer.ibm.com/patterns/ensuring-fairne

A framework for assessing and improving classification fairness.

Interpretable Ml ⭐ 17

Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.

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

Fairbatch ⭐ 16

FairBatch: Batch Selection for Model Fairness (ICLR 2021)

Mlr3fairness ⭐ 13

mlr3 extension for Fairness in Machine Learning

Trusted Ml Pipelines ⭐ 12

Trusted ML Pipeline Tutorial

Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.

Ml_fairness_ethics_explainability ⭐ 10

Fairness, Ethics, Explainability in AI and ML

Responsible Ai Workshop ⭐ 9

Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice

Trusted Ai Workshops ⭐ 9

Introduction to trusted AI. Learn to use fairness algorithms to reduce and mitigate bias in data and models with aif360 and explain models with aix360

Explore/examine/explain/expose your model with the explabox!

Laundryml ⭐ 8

Code for our paper "Fairwashing: the risk of rationalization" (https://arxiv.org/abs/1901.09749) accepted at ICML 2019.

Matching With Gans ⭐ 7

Matching in GAN latent space for better bias benchmarking and semantic image editing. 👶🏻🧒🏾👩🏼‍🦰👱🏽‍♂️👴🏾

Aequitas, a directed fairness testing framework machine learning models.

Bias Detection ⭐ 7

Detection of propaganda or partisan allegiance in natural text.

Fair Classification ⭐ 7

Code for “Fair and Optimal Classification via Post-Processing”.

Shapley_valuation ⭐ 6

PyTorch reimplementation of computing Shapley values via Truncated Monte Carlo sampling from "What is your data worth? Equitable Valuation of Data" by Amirata Ghorbani and James Zou [ICML 2019]

FairGAN: GANs-based Fairness-aware Learning for Recommendations with Implicit Feedback

Monitor Custom Ml Engine With Watson Openscale ⭐ 6

Deploy a Custom Machine Learning engine and Monitor Payload Logging and Fairness using AI OpenScale

Fairml Farm ⭐ 6

A collection of implementations of fair ML algorithms

Canonical_sets ⭐ 5

Exposing Algorithmic Bias with Canonical Sets

Especializacaounifacisa2019 ⭐ 5

Material do Módulo de Machine Learning I - Especialização em Ciência de Dados

Open-source toolkit to help companies implement responsible AI workflows.

Ai Fairness ⭐ 5

Notes, references and materials on AI Fairness that I found useful and helped me in my research. Recommendations are welcome.

Fairness_diagnostics ⭐ 5

Tool to visualize and diagnose fairness issues in machine learning

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