Explainable AI: Building Trust and Transparency with SHAP
In the fast-paced evolution of artificial intelligence (AI), transparency and trust are critical. Machine learning models often act as “black boxes,” making decisions without clearly explaining why. SHAP (SHapley Additive exPlanations) addresses this issue by providing explanations based on game theory, attributing specific feature contributions to individual predictions. This article walks through a hands-on example … Read more