InterpretML

InterpretML is an open-source Python library designed for training inherently interpretable models (glassbox models) and explaining black-box machine learning systems. It provides a unified API for various interpretability techniques, including Explainable Boosting Machines (EBMs), LIME, and SHAP, along with interactive visualizations to help users understand model behavior globally and locally. The library is actively maintained, with frequent minor releases (e.g., several in early 2026), and is currently at version 0.7.8.