SHAP and Shapley Values for Interpretable Machine Learning - Kaggle 30 Days of ML Day 18

Explore SHAP (SHapley Additive exPlanations) and Shapley Values in this 21-minute video tutorial on interpretable machine learning and explainable AI (XAI). Learn why SHAP is necessary, understand its core concepts, and see how it works for local interpretation through practical examples. Dive into Python code for calculating Shapley Values and creating visualizations. Discover alternatives to SHAP and gain insights into making machine learning models more transparent and explainable. Perfect for data scientists and machine learning enthusiasts looking to enhance their understanding of model interpretability techniques.