Interpretable Machine Learning is popular PDF and ePub book, written by Christoph Molnar in 2020, it is a fantastic choice for those who relish reading online the Artificial intelligence genre. Let's immerse ourselves in this engaging Artificial intelligence book by exploring the summary and details provided below. Remember, Interpretable Machine Learning can be Read Online from any device for your convenience.
Interpretable Machine Learning 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.
Detail Book of Interpretable Machine Learning PDF
- Author : Christoph Molnar
- Release : 21 September 2024
- Publisher : Lulu.com
- ISBN : 9780244768522
- Genre : Artificial intelligence
- Total Page : 320 pages
- Language : English
- PDF File Size : 11,9 Mb
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