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Hands-On Neural Networks with Keras

You're reading from   Hands-On Neural Networks with Keras Design and create neural networks using deep learning and artificial intelligence principles

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789536089
Length 462 pages
Edition 1st Edition
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Author (1):
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Niloy Purkait Niloy Purkait
Author Profile Icon Niloy Purkait
Niloy Purkait
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Fundamentals of Neural Networks FREE CHAPTER
2. Overview of Neural Networks 3. A Deeper Dive into Neural Networks 4. Signal Processing - Data Analysis with Neural Networks 5. Section 2: Advanced Neural Network Architectures
6. Convolutional Neural Networks 7. Recurrent Neural Networks 8. Long Short-Term Memory Networks 9. Reinforcement Learning with Deep Q-Networks 10. Section 3: Hybrid Model Architecture
11. Autoencoders 12. Generative Networks 13. Section 4: Road Ahead
14. Contemplating Present and Future Developments 15. Other Books You May Enjoy

Designing a CNN

Now, armed with the intuition of biological vision, we understand how neurons must be organized hierarchically, to detect simple patterns and use these to progressively build more complex patterns corresponding to real-world objects. We also know that we must implement a mechanism for spatial invariance to allow neurons to deal with similar inputs occurring at different spatial locations of a given image. Finally, we are aware that implementing a receptive field for each neuron is useful to achieve a topographical mapping of neurons to spatial locations in the real world, so that nearby neurons may represent nearby regions in the field of vision.

Dense versus convolutional layer

You will recall from the previous...

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