Applied Machine Learning Explainability Techniques

Leverage top XAI frameworks to explain your machine learning models with ease and discover best practices and guidelines to build scalable explainable ML systems Key Features Explore various explainability methods for designing robust and scalable explainable ML systemsUse XAI frameworks such as LIME and SHAP to make ML models explainable to solve practical problemsDesign user-centric explainable ML systems using guidelines provided for industrial applications Book Description Explainable AI (XA