Alternatives and similar repositories for MLWorkshopSeries:

Users that are interested in MLWorkshopSeries are comparing it to the libraries listed below

• dssg / fairness_tutorial
  Hands-on tutorial on ML Fairness
  ☆70Updated last year
• google / ml-fairness-gym
  ☆313Updated last year
• ludovikcoba / recoxplainer
  ☆26Updated 3 years ago
• EthicalML / explainability-and-bias
  ☆101Updated last year
• fair-preprocessing / nips2017
  ☆26Updated 7 years ago
• sisinflab / recsys2021-pursuing-privacy
  Material supporting the tutorial "Pursuing Privacy in Recommender Systems: The View of Users and Researchers from Regulations to Applicat…
  ☆18Updated last year
• socialfoundations / folktables
  Datasets derived from US census data
  ☆251Updated 9 months ago
• MengtingWan / marketBias
  data and source code for "Addressing Marketing Bias in Product Recommendations" WSDM'20
  ☆41Updated 4 years ago
• microsoft / project-azua
  Data Efficient Decision Making
  ☆245Updated 2 years ago
• IBM / inFairness
  PyTorch package to train and audit ML models for Individual Fairness
  ☆64Updated last year
• andreysharapov / xaience
  All about explainable AI, algorithmic fairness and more
  ☆107Updated last year
• gdmarmerola / interactive-intro-rl
  Big Data's open seminars: An Interactive Introduction to Reinforcement Learning
  ☆64Updated 3 years ago
• mbilalzafar / fair-classification
  Python code for training fair logistic regression classifiers.
  ☆189Updated 3 years ago
• flecue / xai-aaai2022
  ☆31Updated 2 years ago
• ChicagoHAI / human-centered-machine-learning
  Schedule and Syllabus for Human-Centered Machine learning.
  ☆183Updated last year
• gpleiss / equalized_odds_and_calibration
  Code and data for the experiments in "On Fairness and Calibration"
  ☆50Updated 2 years ago
• yongkaiwu / FairAI
  This is a collection of papers and other resources related to fairness.
  ☆92Updated last year
• sisinflab / amlrecsys-tutorial
  Tutorial by Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia and Felice Antonio Merra about Adversarial Machine Learning in Recommende…
  ☆25Updated 3 years ago
• lydiatliu / delayedimpact
  Code for reproducing results in Delayed Impact of Fair Machine Learning (Liu et al 2018)
  ☆14Updated 2 years ago
• sisinflab / HandsOn-ECIR2021
  ☆14Updated 4 years ago
• UCLA-StarAI / Density-Estimation-Datasets
  A collection of commonly used datasets as benchmarks for density estimation
  ☆24Updated 5 years ago
• dssg / MLinPractice
  Repository for ML in Practice Course at CMU (10-718)
  ☆58Updated last year
• IBMDeveloperUK / Data-Visualisation-with-Python
  In this workshop we will work with some of the widely used python visualisation packages
  ☆15Updated 3 years ago
• charmlab / recourse
  Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831
  ☆36Updated 2 years ago
• amarasovic / interpretability-literature
  ☆264Updated 5 years ago
• psywaves / EVCF
  Enhancing VAEs for Collaborative Filtering: Flexible Priors & Gating Mechanisms
  ☆43Updated 5 years ago
• mkusner / counterfactual-fairness
  Code for "Counterfactual Fairness" (NIPS2017)
  ☆52Updated 6 years ago
• olivierjeunen / decision-theory-www-2021
  Materials for the "Recommender Systems through the lens of Decision Theory" tutorial delivered at the 30th Web Conference (WWW '21).
  ☆11Updated 3 years ago
• dylan-slack / Fooling-LIME-SHAP
  Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
  ☆82Updated 2 years ago
• gourabkumarpatro / FairRec_www_2020
  Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms
  ☆32Updated 3 years ago