About
The ML Model Explainability Tool is a specialized skill that empowers developers and data scientists to bridge the gap between complex 'black box' machine learning models and actionable human insights. By leveraging advanced techniques such as SHAP and LIME, this skill enables Claude to analyze model behavior, identify the most influential features, and provide clear explanations for specific prediction outcomes. Whether you are debugging model performance, ensuring algorithmic fairness, or communicating technical results to non-technical stakeholders, this tool provides the structured analysis needed to make machine learning systems more transparent and trustworthy.
