Interpretability in Deep Learning Hardback
by Ayush Somani, Alexander Horsch, Dilip K. Prasad
Hardback
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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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In Stock - low on stock, only 1 copy remainingFree UK DeliveryEstimated delivery 2-3 working days
- Format:Hardback
- Pages:466 pages, 172 Illustrations, color; 4 Illustrations, black and white; XX, 466 p. 176 illus., 172 il
- Publisher:Springer International Publishing AG
- Publication Date:01/05/2023
- Category:
- ISBN:9783031206382
Other Formats
- EPUB from £118.58
Information
-
In Stock - low on stock, only 1 copy remainingFree UK DeliveryEstimated delivery 2-3 working days
- Format:Hardback
- Pages:466 pages, 172 Illustrations, color; 4 Illustrations, black and white; XX, 466 p. 176 illus., 172 il
- Publisher:Springer International Publishing AG
- Publication Date:01/05/2023
- Category:
- ISBN:9783031206382