Alternatives and similar repositories for debias-ml:

Users that are interested in debias-ml are comparing it to the libraries listed below

• MI2DataLab / pyBreakDown
  Python implementation of R package breakDown
  ☆42Updated last year
• klemag / PyconUS_2019-model-interpretability-tutorial
  Content for the Model Interpretability Tutorial at Pycon US 2019
  ☆41Updated 8 months ago
• olivkoch / intro-to-reco
  introduction class to recommendation systems
  ☆22Updated 5 years ago
• koaning / scikit-fairness
  this repo might get accepted
  ☆28Updated 4 years ago
• david26694 / sktools
  Helpers for scikit learn
  ☆16Updated 2 years ago
• aredier / trelawney
  General Interpretability Package
  ☆58Updated 2 years ago
• jphall663 / hc_ml
  Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
  ☆22Updated 5 years ago
• jphall663 / secure_ML_ideas
  Practical ideas on securing machine learning models
  ☆36Updated 3 years ago
• georgian-io-archive / automl_benchmark
  Distributed, large-scale, benchmarking framework for rigorous assessment of automatic machine learning repositories, projects, and librar…
  ☆30Updated 2 years ago
• jphall663 / xai_misconceptions
  Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!
  ☆28Updated 5 years ago
• Informationsfabrik / feature-engineering
  ☆14Updated 5 years ago
• fastai / ethics.fast.ai
  The fast.ai data ethics course
  ☆15Updated 2 years ago
• ShopRunner / octopod
  Train multi-task image, text, or ensemble (image + text) models
  ☆45Updated last year
• jphall663 / kdd_2019
  Paper and talk from KDD 2019 XAI Workshop
  ☆20Updated 4 years ago
• jphall663 / responsible_xai
  Guidelines for the responsible use of explainable AI and machine learning.
  ☆17Updated 2 years ago
• ericmjl / causality
  In which I play with the ideas surrounding causality
  ☆51Updated 2 years ago
• numeristical / introspective
  Repo for the ML_Insights python package
  ☆150Updated last year
• muellerzr / fastai2-Tabular-Baselines
  A few baselines with a standard tabular model
  ☆38Updated 4 years ago
• morganmcg1 / ntentional
  The ntentional blog - a machine learning journey
  ☆23Updated 2 years ago
• muellerzr / fastai2_tabular_hybrid
  Developing and integrating methods for fastai2 tabular with other datatypes
  ☆26Updated 2 years ago
• jandremarais / TabularLearner
  Repo for work on deep learning for tabular data
  ☆14Updated 4 years ago
• Affirm / shparkley
  Spark implementation of computing Shapley Values using monte-carlo approximation
  ☆74Updated 2 years ago
• summerscope / fair-ml-reading-group
  Reading history for Fair ML Reading Group in Melbourne
  ☆36Updated 3 years ago
• FlorianWilhelm / bhm-at-scale
  🪜 Bayesian Hierarchical Models at Scale
  ☆52Updated 3 years ago
• Shivanandroy / CategoricalEmbedder
  Categorical Embedder is a python package that let's you convert your categorical variables into numeric via Neural Networks
  ☆25Updated 5 years ago
• Pak911 / fastai-shared-notebooks
  ☆20Updated 5 years ago
• alteryx / categorical_encoding
  Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library
  ☆51Updated 2 years ago
• capitalone / global-attribution-mapping
  GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations
  ☆33Updated 3 months ago
• weehyong / MLScore
  Know your ML Score based on Sculley's paper
  ☆34Updated 5 years ago
• AidanCooper / shap-clustering
  How to use SHAP values for better cluster analysis
  ☆57Updated 2 years ago