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An Automated Machine Learning Python package for tabular data with feature engineering, hyperparameter tuning, explanations, and automatic documentation.
A curated collection of research papers, books, courses, and Python libraries for explainable AI (XAI) and machine learning interpretability.
A model-agnostic method for generating high-precision rule-based explanations for black-box classifier predictions.
An engine for ML/data tracking, visualization, explainability, drift detection, and dashboards, integrated with Polyaxon.
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