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Interpretable Machine Learning-Book - Research Book

Interpretable Machine Learning-Book - Research Book

Trending Research Book in Interpretable Machine Learning-Book

Author(s) Name:  Christoph Molnar

About the Book:

   This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

ISBN:  9780244768522

Publisher:  Leanpub

Year of Publication:  2020

Book Link:  Home Page Url