interpretable_machine_learning_with_python
ML model transparency
Teaching software developers how to build transparent and explainable machine learning models using Python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
673 stars
42 watching
207 forks
Language: Jupyter Notebook
last commit: 5 months ago
Linked from 2 awesome lists
accountabilitydata-miningdata-sciencedecision-treefairnessfatmlgradient-boosting-machineh2oimlinterpretabilityinterpretableinterpretable-aiinterpretable-machine-learninginterpretable-mllimemachine-learningmachine-learning-interpretabilitypythontransparencyxai
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