Interpreting Machine Learning Models - Learn Model Interpretability and Explainability Methods

Interpreting Machine Learning Models: Learn Model Interpretability and Explainability Methods
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English | 2022 | ISBN: 1484278011 | 355 pages | True (PDF,EPUB) | 27.23 MB

Understand model interpretability methods and apply the most suitable one for your machine learning project. This book details the concepts of machine learning interpretability along with different types of explainability algorithms.

You’ll begin by reviewing the theoretical aspects of machine learning interpretability. In the first few sections you’ll learn what interpretability is, what the common properties of interpretability methods are, the general taxonomy for classifying methods into different sections, and how the methods should be assessed in terms of human factors and technical requirements. Using a holistic approach featuring detailed examples, this book also includes quotes from actual business leaders and technical experts to showcase how real life users perceive interpretability and its related methods, goals, stages, and properties.