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awesome-Interpretable-ML

A curated list for interpretable machine learning
https://github.com/Henrilin28/awesome-Interpretable-ML

Last synced: 4 days ago
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Table of Contents
- Python packages
  - lime
  - sklearn-expertsys
  - FairML - to-end toolbox for auditing predictive models by quantifying the relative significance of the model’s inputs.
  - Edward
  - ML Insights - Learn and XGBoost library. It should work with any machine learning library that has a predict and predict_proba methods for regression and classification estimators.
  - SNAP: node2vec
  - Stan
  - Shap
- Videos and Lectures
  - Andrew Rowan - Bayesian Deep Learning with Edward (and a trick using Dropout)

Programming Languages

Jupyter Notebook 2 Python 2 JavaScript 1

Categories

Table of Contents 9 License 1

Sub Categories

Python packages 8 Videos and Lectures 1 Contributing 1

Keywords

deep-learning 2 machine-learning 2 auditing-predictive-models 1 discrimination 1 fairness 1 model-criticism 1 prediction-model 1 toolbox 1 bayesian-methods 1 data-science 1 neural-networks 1 probabilistic-programming 1 statistics 1 tensorflow 1 explainability 1 gradient-boosting 1 interpretability 1 shap 1 shapley 1