Publisher | Springer, Berlin |
Year | |
Pages | 285 |
Version | hardback |
Language | English |
ISBN | 9783030665180 |
Categories |
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.
Advanced Deep Learning for Engineers and Scientists: A Practical Approach
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.