Advanced Deep Learning for Engineers and Scientists
A Practical Approach
Series: EAI/Springer Innovations in Communication and Computing;
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Product details:
- Edition number 1st ed. 2021
- Publisher Springer International Publishing
- Date of Publication 26 July 2022
- Number of Volumes 1 pieces, Book
- ISBN 9783030665210
- Binding Paperback
- See also 9783030665180
- No. of pages285 pages
- Size 235x155 mm
- Weight 562 g
- Language English
- Illustrations XVII, 285 p. 281 illus., 261 illus. in color. Illustrations, black & white 282
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Long description:
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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Table of 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.
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