Using SHAP Values to Explain How Your Machine Learning Model Works, by Vinícius Trevisan

Introduction to Explainable AI (Explainable Artificial Intelligence or XAI) - 10 Senses

Interpreting ROC Curve and ROC AUC for Classification Evaluation, by Vinícius Trevisan

Evaluating classification models with Kolmogorov-Smirnov (KS) test, by Vinícius Trevisan

List: Feature Importance with SHAP, Curated by Lars ter Braak

Using SHAP Values to Explain How Your Machine Learning Model Works — Vinicius Trevisan

Introduction to Explainable AI (Explainable Artificial Intelligence or XAI) - 10 Senses

Using SHAP Values to Explain How Your Machine Learning Model Works, by Vinícius Trevisan

List: Data science, Curated by Bodil Elbrink

Is your ML model stable? Checking model stability and population drift with PSI and CSI, by Vinícius Trevisan

List: SHAP, Curated by Gabriella Freitas