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Neural networks and deep learning: a textbook

By: Material type: TextTextPublication details: Switzerland: Springer, 2018Edition: 2ndDescription: xxiii, 500p.: 6x11x2; HardcoverISBN:
  • 9783031296413
Subject(s): DDC classification:
  • 006.32 AGG/NEU
Summary: This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Deep learning methods for various data domains, such as text, images, and graphs are presented in detail.
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Item type Current library Call number Status Notes Barcode
Reference Reference Central Library NIT Goa General stacks 006.32 AGG/NEU (Browse shelf(Opens below)) Not for loan Reference Book Rack number 37(B) 11020

This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications.
The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Deep learning methods for various data domains, such as text, images, and graphs are presented in detail.

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