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Hands-On Neural Networks with Keras

You're reading from  Hands-On Neural Networks with Keras

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789536089
Pages 462 pages
Edition 1st Edition
Languages
Author (1):
Niloy Purkait Niloy Purkait
Profile icon Niloy Purkait

Table of Contents (16) Chapters

Preface 1. Section 1: Fundamentals of Neural Networks
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

Knowing our tools

We will mainly be working with the two most popular deep learning frameworks that exist, and are freely available to the public at large. This does not mean that we will completely limit our implementations and exercises to these two platforms. It may well occur that we experiment with other prominent deep learning frameworks and backends. We will, however, try to use either TensorFlow or Keras, due to their widespread popularity, large support community, and flexibility in interfacing with other prominent backend and frontend frameworks (such as Theano, Caffe, or Node.js, respectively). We will now provide a little background information on Keras and TensorFlow:

Keras

Many have named Keras the lingua franca...

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