Alternatives and similar repositories for Ethical-AI-Standard:

Users that are interested in Ethical-AI-Standard are comparing it to the libraries listed below

• jphall663 / secure_ML_ideas
  Practical ideas on securing machine learning models
  ☆36Updated 3 years ago
• koaning / scikit-fairness
  this repo might get accepted
  ☆29Updated 4 years ago
• zelros / cinnamon
  CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
  ☆77Updated 2 years ago
• jphall663 / GWU_rml
  ☆35Updated last week
• pcerda / string_categorical_encoders
  Scripts for paper "Encoding high-cardinality string categorical variables"
  ☆24Updated 5 years ago
• jphall663 / kdd_2019
  Paper and talk from KDD 2019 XAI Workshop
  ☆20Updated 4 years ago
• XAI-ANITI / ethik
  A toolbox for fair and explainable machine learning
  ☆55Updated 8 months ago
• aromain / intermarche_challenge
  [Intemarché] Sales forecasting challenge
  ☆11Updated 3 years ago
• pmbaumgartner / binder-notebooks
  Notebooks configured to be run with Binder, usually found on my blog.
  ☆42Updated last year
• koaning / tokenwiser
  Bag of, not words, but tricks!
  ☆68Updated last year
• ottogroup / dstoolbox
  Tools that make working with scikit-learn and pandas easier.
  ☆44Updated 10 months ago
• ShopRunner / octopod
  Train multi-task image, text, or ensemble (image + text) models
  ☆45Updated last year
• dkn22 / embedder
  Embed categorical variables via neural networks.
  ☆59Updated last year
• oegedijk / rule_estimator
  A scikit-learn compatible estimator based on business-rules with interactive dashboard included
  ☆28Updated 3 years ago
• salimamoukou / acv00
  ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…
  ☆100Updated 2 years ago
• jphall663 / xai_misconceptions
  Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!
  ☆28Updated 5 years ago
• koaning / sentimany
  Just another sentiment wrapper.
  ☆17Updated 3 years ago
• yeounoh / slicefinder
  automatic data slicing
  ☆35Updated 3 years ago
• MaxHalford / naked
  The simplest way to deploy a machine learning model
  ☆23Updated 2 years ago
• apmoore1 / fiesta
  Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms
  ☆14Updated 2 years ago
• ehsanma / IDS-566
  Advanced Text Analytics for Business
  ☆15Updated 6 years ago
• MI2DataLab / pyBreakDown
  Python implementation of R package breakDown
  ☆42Updated last year
• hanneshapke / Deploying-Deep-Learning-Models
  Strategies to deploy deep learning models
  ☆27Updated 6 years ago
• ilias-ant / adversarial-validation
  A tiny framework to perform adversarial validation of your training and test data.
  ☆20Updated last month
• Machine-Learning-Tokyo / ML_Fairness_Ethics_Explainability
  Fairness, Ethics, Explainability in AI and ML
  ☆22Updated 4 years ago
• LDSSA / heroku-model-deploy
  Deploy a scikit model using heroku and Flask
  ☆14Updated last year
• ivylee / model-cards-and-datasheets
  A collection of machine learning model cards and datasheets.
  ☆72Updated 8 months ago
• rungalileo / bulk-labeling
  A tool for quickly adding labels to unlabeled datasets
  ☆20Updated last year
• aredier / trelawney
  General Interpretability Package
  ☆58Updated 2 years ago
• AMDonati / ODSC2019-DL-models-NLP
  materials for my workshop "Latest Deep Learning Models for NLP" @ the European Open Data Science Conference 2019
  ☆10Updated 5 years ago