Running Clarify Jobs to Extract Interpretability & Bias Metrics

Now that we understand the importance of model explainability and fairness, it’s time to generate real interpretability and bias insights using AWS SageMaker Clarify. In this part, you’ll configure and launch Clarify processing jobs on a trained ML model. These jobs will compute feature attributions using SHAP values, as well as bias metrics across sensitive attributes.