Demystifying The Machine: Building Your Own Model Explainability Tool

This article provides a step-by-step guide for developing a model explainability tool for machine learning models. It emphasizes the importance of transparency and interpretability in AI and introduces the SHAP library as a powerful tool for achieving this. The guide uses Python and scikit-learn to create a sample machine learning model and demonstrates how to train it on a dummy dataset.