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Название: Interpreting Machine Learning Models With SHAP : A Guide With Python Examples And Theory On Shapley Values
Автор: Christoph Molnar
Издательство: Leanpub
Год: 2023-08-01
Страниц: 216
Язык: английский
Формат: pdf (true), epub + extras
Размер: 18.4 MB
Master Machine Learning interpretability with this comprehensive guide to SHAP – your tool to communicating model insights and building trust in all your Machine Learning applications. Machine Learning is transforming fields from healthcare diagnostics to climate change predictions through their predictive performance. However, these complex Machine Learning models often lack interpretability, which is becoming more essential than ever for debugging, fostering trust, and communicating model insights. Introducing SHAP, the Swiss army knife of Machine Learning interpretability. This book is for data scientists, statisticians, machine learners, and anyone who wants to learn how to make machine learning models more interpretable. Ideally, you are already familiar with Machine Learning to get the most out of this book. And you should know your way around Python to follow the code examples.
Автор: Christoph Molnar
Издательство: Leanpub
Год: 2023-08-01
Страниц: 216
Язык: английский
Формат: pdf (true), epub + extras
Размер: 18.4 MB
Master Machine Learning interpretability with this comprehensive guide to SHAP – your tool to communicating model insights and building trust in all your Machine Learning applications. Machine Learning is transforming fields from healthcare diagnostics to climate change predictions through their predictive performance. However, these complex Machine Learning models often lack interpretability, which is becoming more essential than ever for debugging, fostering trust, and communicating model insights. Introducing SHAP, the Swiss army knife of Machine Learning interpretability. This book is for data scientists, statisticians, machine learners, and anyone who wants to learn how to make machine learning models more interpretable. Ideally, you are already familiar with Machine Learning to get the most out of this book. And you should know your way around Python to follow the code examples.