Alternatives and similar repositories for GWU_rml

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

• jphall663 / secure_ML_ideas
  Practical ideas on securing machine learning models
  ☆36Updated 4 years ago
• jphall663 / hc_ml
  Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
  ☆22Updated 5 years ago
• MI2DataLab / pyBreakDown
  Python implementation of R package breakDown
  ☆43Updated 2 years ago
• alteryx / predict-correct-answer
  Predict whether a student will correctly answer a problem based on past performance using automated feature engineering
  ☆32Updated 5 years ago
• jphall663 / kdd_2019
  Paper and talk from KDD 2019 XAI Workshop
  ☆20Updated 5 years ago
• fastforwardlabs / couples-lime
  Notebook demonstrating use of LIME to interpret a model of long-term relationship success
  ☆24Updated 7 years ago
• jphall663 / responsible_xai
  Guidelines for the responsible use of explainable AI and machine learning.
  ☆17Updated 2 years ago
• unravelin / code-test-data-science
  Data Scientist code test
  ☆19Updated 5 years ago
• alteryx / categorical_encoding
  Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library
  ☆51Updated 3 years ago
• klemag / PyconUS_2019-model-interpretability-tutorial
  Content for the Model Interpretability Tutorial at Pycon US 2019
  ☆41Updated last year
• WinVector / pyvtreat
  vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distr…
  ☆121Updated 7 months ago
• drivendataorg / power-laws-cold-start
  ☆23Updated last year
• jphall663 / diabetes_use_case
  Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/
  ☆27Updated last year
• jphall663 / xai_misconceptions
  Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!
  ☆28Updated 6 years ago
• YuriyGuts / odsc-target-leakage-workshop
  Workshop on Target Leakage in Machine Learning I taught at ODSC Europe 2018 (London) and ODSC East 2019, 2020 (Boston)
  ☆37Updated 5 years ago
• numeristical / introspective
  Repo for the ML_Insights python package
  ☆152Updated 4 months ago
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆52Updated 4 years ago
• Vishwacorp / nyc_uber_forecasting
  Forecasting Uber demand in NYC neighborhoods
  ☆34Updated 7 years ago
• navdeep-G / interpretable-ml
  Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
  ☆21Updated 3 years ago
• tdpetrou / integrating-pandas-with-scikit-learn
  Tutorial covering a new workflow available going from pandas to scikit-learn
  ☆40Updated 2 years ago
• h2oai / tutorials
  This is a repo for all the tutorials put out by H2O.ai. This includes learning paths for Driverless AI, H2O-3, Sparkling Water and more..…
  ☆134Updated last year
• CamDavidsonPilon / PyDataNY_2019_tutorial
  Repo for PyData 2019 Tutorial - New Trends in Estimation and Inference
  ☆26Updated 5 years ago
• h2oai / driverlessai-tutorials
  H2OAI Driverless AI Code Samples and Tutorials
  ☆37Updated 9 months ago
• amueller / aml
  Applied Machine Learning with Python
  ☆80Updated last year
• sachinruk / bayes_school
  ☆16Updated 6 years ago
• luke14free / bulldog
  State management framework for Data Science & Analytics
  ☆19Updated 5 years ago
• ericmjl / causality
  In which I play with the ideas surrounding causality
  ☆53Updated 3 years ago
• EricSchles / drifter_ml
  A machine learning testing framework for sklearn and pandas. The goal is to help folks assess whether things have changed over time.
  ☆102Updated 3 years ago
• ModelOriented / SAFE
  Surrogate Assisted Feature Extraction
  ☆37Updated 4 years ago
• harnav / pydata-docker-tutorial
  Tutorial given at PyData LA 2018
  ☆97Updated last year