Implementing Model Explainability
Demonstrates how to add explainers to AI models using MimicExplainer for black-box models, TabularExplainer with SHAP integration, and PFIExplainer for permutation-based analysis. Shows uploading explanations to experiment runs, visualizing in Azure ML studio, and adding lightweight scoring explainers to inference pipelines.
