Interpretability in Deep Learning

Interpretability in Deep Learning 1st ed. 2023 Edition
by Ayush Somani(Author), Alexander Horsch(Author), Dilip K. Prasad(Author)
Publisher Finelybook 出版社: ; 1st ed. 2023 edition (May 1, 2023)
Language 语言: English
pages 页数: 486 pages
ISBN-10 书号: 303120638X
ISBN-13 书号: 9783031206382

Book Description
This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network architectures. In addition, it includes several case studies from application-oriented articles in the fields of computer vision, optics and machine learning related topic.

The book can be used as a monograph on interpretability in deep learning covering the most recent topics as well as a textbook for graduate students. Scientists with research, development and application responsibilities benefit from its systematic exposition.

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