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eif

Extended Isolation Forest for Anomaly Detection

eurybia

⚓ Eurybia monitors model drift over time and securizes model deployment with data validation

examples

explainability-and-bias

fad

Fairness through Adversarial Discrimination

fair-classification

Python code for training fair logistic regression classifiers.

fair_erm

Fair Empirical Risk Minimization (FERM)

fairai

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

fairclassifier

An open source package that evaluate the fairness of a Neural Network using a fairness metric called p% rule.

fairlearn

A Python package that implements a variety of algorithms that mitigate unfairness in supervised machine learning.

fairmlbook.github.io

fairness-comparison

Comparing fairness-aware machine learning techniques.

fairness-in-classification-and-representation-learning

Implementation of Fairness method for Classification Task

fairness-in-ml

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

fairness-indicators

Tensorflow's Fairness Evaluation and Visualization Toolkit

fairtest

fb-glg-project

feature-engineering

featureselectionga

Feature Selection using Genetic Algorithm (DEAP Framework)

flexible-fairness-constraints

Code for ICML2019 Paper "Compositional Invariance Constraints for Graph Embeddings"

fsi-samples

A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Numba, cuDF, and Dask.

gerryfair

library for fair auditing and learning of classifiers with respect to rich subgroup fairness.

glg-topic-modeling

Deployment of a UI on ElasticBeanstalk and Sagemaker Endpoints for Named Entity Recognition (NER) with BERT and Topic Modelling with Latent Dirichlet Allocation (gensim LDA-multicore)

google-research

Google Research

gpt-3

GPT-3: Language Models are Few-Shot Learners

graph_nets

Build Graph Nets in Tensorflow

han

Heterogeneous Graph Neural Network

hudson-and-thames-research

Research Repo (Archive)

interpretable-ml-book

Book about interpretable machine learning

interpretable_machine_learning_with_python

Practical techniques for training interpretable ML models, explaining ML models, and debugging ML models.