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Kniha Interpretability in Deep Learning Dilip K. Prasad

Interpretability in Deep Learning

Autor: Dilip K. Prasad, Alexander Horsch
Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: Springer International Publishing
Dostupnost: Skladem u dodavatele
Odesíláme za 8-11 dnů
3 654 Kč
This book is a comprehensive curation, exposition and illustrative discussion of recent research too...

Informace o knize

Autor
Dilip K. Prasad, Alexander Horsch
Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2023
Stránek
488
EAN
9783031206412
ISBN
303120641X
Enbook ID
45871161
Vydavatel
Springer International Publishing
Hmotnost
821
Rozměry
155 x 235 x 25

Kompletní popis

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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