Interpretable Machine Learning: A Guide For Making Black Box Models Explainable
A guide to interpreting machine learning models and making black box predictions explainable and transparent.
About This Book
Interpretable Machine Learning provides guidance on understanding and explaining complex machine learning models.
The book addresses the challenges of black box models and offers methods to increase transparency.
Readers learn approaches for interpreting predictions and building trust in automated systems.
Topics include model-agnostic methods and techniques for visualizing model behavior.
Reviews
No reviews yet. Be the first to review this book!