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Advanced Deep Learning for Engineers and Scientists A Practical Approach

Title
Advanced Deep Learning for Engineers and Scientists [electronic resource] : A Practical Approach / edited by Kolla Bhanu Prakash, Ramani Kannan, S.Albert Alexander, G. R. Kanagachidambaresan.
ISBN
9783030665197
Edition
1st ed. 2021.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2021.
Physical Description
1 online resource (XVII, 285 p.) 281 illus., 61 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
August 13, 2021
Series
EAI/Springer Innovations in Communication and Computing,
EAI/Springer Innovations in Communication and Computing,
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.
Citation

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