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jphall663
interpretable_machine_learning_with_python jphall663
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Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
h2o iml xai lime fatml python fairness data-mining data-science transparency decision-tree interpretable accountability interpretability interpretable-ai interpretable-ml machine-learning gradient-boosting-machine interpretable-machine-learning machine-learning-interpretability
Created 2018-03-14
169 commits to master branch, last one about a year ago