You might also like

More about Interpretability in Deep Learning

• Book details
• Synopsis
• Trending among others

You get 398 loyalty points

Book synopsis

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.

 

 

Book details

Book category Books in German Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Informatik

• Full title: Interpretability in Deep Learning
• Author: Dilip K. Prasad, Alexander Horsch
• Language: English
• Binding: Paperback
• Number of pages: 488
• EAN: 9783031206412
• ISBN: 303120641X
• ID: 45871161
• Publisher: Springer International Publishing
• Weight: 821 g
• Dimensions: 235 × 155 × 25 mm
• Date of publishing: 01. June 2023

Trending among others

---

---

---