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Principles and Practice of Explainable Machine Learning
A survey to help industry practitioners understand the field of explainable machine learning better and apply the right tools.
interpretability explainability survey paper
A Survey of the State of Explainable AI for NLP
Overview of the operations and explainability techniques currently available for generating explanations for NLP model predictions.
interpretability natural-language-processing explainability survey
AllenNLP Interpret
A Framework for Explaining Predictions of NLP Models
interpretability explainability natural-language-processing api
SHAP: SHapley Additive exPlanations
A game theoretic approach to explain the output of any machine learning model.
interpretability shap explainability gradient-boosting
Visualization toolkit for neural networks in PyTorch
interpretability computer-vision pytorch flashtorch
GNNExplainer: Generating Explanations for Graph Neural Networks
General tool for explaining predictions made by graph neural networks (GNNs).
graph-neural-networks interpretability explainability graphs
Explainable Deep Learning: A Field Guide for the Uninitiated
A field guide to deep learning explainability for those uninitiated in the field.
interpretability explainability deep-learning survey
Fairness and Machine Learning
This book gives a perspective on machine learning that treats fairness as a central concern rather than an afterthought.
fairness machine-learning bias privacy
Fit interpretable machine learning models. Explain blackbox machine learning.
interpretability explainability lime shap
Identification of contributing features towards the rupture risk prediction of intracranial aneurysms using LIME explainer
interpretability machine-learning lime healthcare
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