Interpretable Machine Learning mobi epub
分类标签：学习教育
内容简介：
Machine learning has great potential for improving products, processes and research. But computers
usually do not explain their predictions which is a barrier to the adoption of 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 modelagnostic 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.
The book focuses on machine learning models for tabular data (also called relational or structured
data) and less on computer vision and natural language processing tasks. Reading the book is
recommended for machine learning practitioners, data sci
Machine learning has great potential for improving products, processes and research. But computers
usually do not explain their predictions which is a barrier to the adoption of 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 modelagnostic 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.
The book focuses on machine learning models for tabular data (also called relational or structured
data) and less on computer vision and natural language processing tasks. Reading the book is
recommended for machine learning practitioners, data sci
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2、本书为网友分享，可能出现各种错误，点这里报错 我们会尽快修复
3、若无特别说明，同一本书的多个格式内容一样，根据需要下载一个即可。
4、如何阅读不同格式的电子书
5、kindle推送只支持mobi/txt/pdf格式
iphone/ipad系统默认safari浏览器下载功能残废，只能下载epub/pdf，点击“下载” > 等待 > “用ibooks打开”；其他格式需安装QQ、UC等浏览器等下载
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