Interpretable Machine Learning

This book PDF is perfect for those who love Artificial intelligence genre, written by Christoph Molnar and published by Lulu.com which was released on 29 March 2024 with total hardcover pages 320. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Interpretable Machine Learning books below.

Interpretable Machine Learning
Author : Christoph Molnar
File Size : 42,8 Mb
Publisher : Lulu.com
Language : English
Release Date : 29 March 2024
ISBN : 9780244768522
Pages : 320 pages
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Interpretable Machine Learning by Christoph Molnar Book PDF Summary

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.

Interpretable Machine Learning

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

Get Book
Interpretable Machine Learning with Python

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ECML PKDD 2020 Workshops

This volume constitutes the refereed proceedings of the workshops which complemented the 20th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2020. Due to the COVID-19 pandemic the conference and workshops were held online. The 43 papers presented in volume were carefully reviewed and

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Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning

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