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Advanced Deep Learning for Engineers and Scientists : A Practical Approach / edited by Kolla Bhanu Prakash, Ramani Kannan, S.Albert Alexander, G. R. Kanagachidambaresan

Contributor(s): Prakash, Kolla Bhanu, editor literario | Kannan, Ramani, editor literario | Alexander, S. Albert, editor literario | Kanagachidambaresan, G. R., editor literario
Material type: materialTypeLabelE-bookSeries: (EAI/Springer Innovations in Communication and Computing, 2522-8609); (Engineering (SpringerNature-11647)); (Engineering (R0) (SpringerNature-43712)).Publisher: Cham : Springer International Publishing, 2021Edition: First edition 2021.Description: 1 recurso en línea (XVII, 285 páginas) : 281 ilustraciones, 261 ilustraciones a color.ISBN: 9783030665197.Subject: Aprendizaje automáticoOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction -- Introduction to ANN -- Introduction to Deep Learning -- Deep Soft Computing using Python -- Working with Keras -- Deep learning Applications using Python -- Advanced Deep learning techniques -- Conclusion.
Abstract: This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in deep learning. The authors start with the fundamentals, architectures, tools needed for effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python. They proceed with advanced concepts with hands-on sessions for deep learning. Engineers, scientists, researches looking for a practical approach to deep learning will enjoy this book. Presents practical basics to advanced concepts in deep learning and how to apply them through various projects; Discusses topics such as deep learning in smart grids and renewable energy & sustainable development; Explains how to implement advanced techniques in deep learning using Pytorch, Keras, Python programming.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q325.5 2021 EB (Browse shelf(Opens below)) Acceso electrónico eBook.11012438
Total holds: 0

Introduction -- Introduction to ANN -- Introduction to Deep Learning -- Deep Soft Computing using Python -- Working with Keras -- Deep learning Applications using Python -- Advanced Deep learning techniques -- Conclusion.

This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in deep learning. The authors start with the fundamentals, architectures, tools needed for effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python. They proceed with advanced concepts with hands-on sessions for deep learning. Engineers, scientists, researches looking for a practical approach to deep learning will enjoy this book. Presents practical basics to advanced concepts in deep learning and how to apply them through various projects; Discusses topics such as deep learning in smart grids and renewable energy & sustainable development; Explains how to implement advanced techniques in deep learning using Pytorch, Keras, Python programming.

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