• InterpretML: An open-source library for understanding and interpreting machine learning models using methods like SHAP and LIME.
• Explainable Boosting Machine (EBM): A glass-box model that allows data analysts to clearly understand the impact of each feature on model predictions.
• Azure Machine Learning Interpretability Toolkit: Offers a suite of tools for investigating model predictions, enabling transparency in machine learning workflows.