Alternatives and similar repositories for fair-ml-reading-group

Users that are interested in fair-ml-reading-group are comparing it to the libraries listed below

• navdeep-G / interpretable-ml
  Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
  ☆21Updated 3 years ago
• microsoft / AdversarialGMM
  Minimax Estimation of Conditional Moment Models
  ☆30Updated 2 years ago
• tansey / functionalmf
  Functional matrix factorization via Bayesian tensor filtering
  ☆13Updated 2 years ago
• capitalone / global-attribution-mapping
  GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations
  ☆34Updated 2 months ago
• jphall663 / secure_ML_ideas
  Practical ideas on securing machine learning models
  ☆36Updated 4 years ago
• Coleridge-Initiative / rclc
  Rich Context leaderboard competition, including the corpus and current SOTA for required tasks.
  ☆21Updated 4 years ago
• leenamurgai / debias-ml
  A practical, explainable and effective method for reducing bias in machine learning algorithms.
  ☆21Updated 5 years ago
• wilsonjr / ClusterShapley
  Explaining dimensionality results using SHAP values
  ☆54Updated 6 months ago
• pcerda / string_categorical_encoders
  Scripts for paper "Encoding high-cardinality string categorical variables"
  ☆24Updated 5 years ago
• ljvmiranda921 / vs-split
  A Python library for creating adversarial splits
  ☆13Updated 2 years ago
• slds-lmu / code_pitfalls_iml
  This repository contains the code for all figures in the paper "General Pitfalls of Model-agnostic Interpretation Methods for Machine Lea…
  ☆15Updated 3 years ago
• google-research / sloe-logistic
  ☆29Updated last year
• ShopRunner1 / octopod
  Train multi-task image, text, or ensemble (image + text) models
  ☆45Updated last year
• jameslamb / lightgbm-dask-testing
  Test LightGBM's Dask integration on different cluster types
  ☆12Updated last week
• koaning / brent
  bayesian graphical modelling and a bit of do-calculus for discrete data.
  ☆27Updated 5 years ago
• alteryx / predict-correct-answer
  Predict whether a student will correctly answer a problem based on past performance using automated feature engineering
  ☆32Updated 4 years ago
• jphall663 / kdd_2019
  Paper and talk from KDD 2019 XAI Workshop
  ☆20Updated 5 years ago
• MI2DataLab / pyBreakDown
  Python implementation of R package breakDown
  ☆43Updated 2 years ago
• oegedijk / rule_estimator
  A scikit-learn compatible estimator based on business-rules with interactive dashboard included
  ☆28Updated 3 years ago
• morganmcg1 / ntentional
  The ntentional blog - a machine learning journey
  ☆23Updated 2 years ago
• LeihuaYe / Causal-Inference-Using-Quasi-Experimental-Methods
  Causal Inference Using Quasi-Experimental Methods
  ☆20Updated 4 years ago
• aschleg / hypothetical
  Hypothesis and statistical testing in Python
  ☆64Updated 4 years ago
• sscardapane / hydra-tutorial
  Companion code for a tutorial on using Hydra.
  ☆29Updated 4 years ago
• poloclub / people-map
  Visualization Tool for Mapping Out Researchers using Natural Language Processing
  ☆56Updated last year
• SelfExplainML / Aletheia
  A Python package for unwrapping ReLU DNNs
  ☆70Updated last year
• realrate / Causing
  Causing: CAUsal INterpretation using Graphs
  ☆58Updated last month
• godatadriven / asekuro
  A utility tool to automate certain tasks with Jupyter notebooks.
  ☆9Updated last year
• weehyong / MLScore
  Know your ML Score based on Sculley's paper
  ☆34Updated 6 years ago
• stanfordmlgroup / risk-adjustment-ml
  Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments.
  ☆12Updated 5 years ago
• outerbounds / nbdoc
  Generate beautiful, testable documentation with Jupyter Notebooks
  ☆21Updated 2 years ago