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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

Converging a model

Next, you can make the model converge on this output class to visualize what the model thinks is a leopard (or another output class) after many iterations of convergence. You can define how long you want your model to converge through the max_iter argument, as shown here:

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