Interpreting Machine Learning Models (ePub)
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Understand model interpretability methods and apply the most suitable one for your machine learning project. This book details the concepts of machine learning interpretability along with different types of explainability algorithms.
You'll begin by reviewing the theoretical aspects of machine learning interpretability. In the first few sections you'll learn what interpretability is, what the common properties of interpretability methods are, the general taxonomy for classifying methods into different sections, and how the methods should be assessed in terms of human factors and technical requirements. Using a holistic approach featuring detailed examples, this book also includes quotes from actual business leaders and technical experts to showcase how real life users perceive interpretability and its related methods, goals, stages, and properties.
Progressing through the book, you'll dive deep into the technical details of the interpretability domain. Starting offwith the general frameworks of different types of methods, you'll use a data set to see how each method generates output with actual code and implementations. These methods are divided into different types based on their explanation frameworks, with some common categories listed as feature importance based methods, rule based methods, saliency maps methods, counterfactuals, and concept attribution. The book concludes by showing how data effects interpretability and some of the pitfalls prevalent when using explainability methods.
You will:
- Understand machine learning model interpretability
- Explore the different properties and selection requirements of various interpretability methods
- Review the different types of interpretability methods used in real life by technical experts
- Interpret the output of various methods and understand the underlying problems
Anirban's interests include learning about new technologies and disruptive start-ups. In his spare time he loves networking with people. On the personal side, Anirban loves sports, and is a big follower of soccer/football (Argentina and Manchester United are his favorite teams).
Email: aninandi1983@gamil.com
Linekdln: https://www.linkedin.com/in/anirban-nandi-89a36ab7/
Aditya Kumar Pal works as a Lead Data Scientist with Rakuten at their Bangalore office. Aditya has a rich experience of more than 8 years in domain of Data Sciences and Business Analytics. He has worked with more than 50 stakeholders over the past 8 years to solve their problems using data and algorithms across multiple functions such as customer analytics, pricing analytics, assortment analytics and marketing analytics etc.Couple of years back,
Email - aditya.nitrr@gmail.com
Linkedin - https://www.linkedin.com/in/aditya-kumar-pal-1423624a
- Autoren: Anirban Nandi , Aditya Kumar Pal
- 2022, 1st ed, 343 Seiten, Englisch
- Verlag: APress
- ISBN-10: 148427802X
- ISBN-13: 9781484278024
- Erscheinungsdatum: 01.01.2022
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: ePub
- Grösse: 12 MB
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