Interpretable Machine Learning with Python Second Edition: Build explainable, fair, and robust high performance models hands on, real world examples

This hands-on book will help you make your machine learning models fairer, safer, and more reliable and in turn improve business outcomes. Every chapter introduces a new mission where you learn how to apply interpretation methods to realistic use cases with methods that work for any model type as well as methods specific for deep neural networks.