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Hands-On Deep Learning Architectures with Python

You're reading from   Hands-On Deep Learning Architectures with Python Create deep neural networks to solve computational problems using TensorFlow and Keras

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781788998086
Length 316 pages
Edition 1st Edition
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Authors (2):
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Saransh Mehta Saransh Mehta
Author Profile Icon Saransh Mehta
Saransh Mehta
Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
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Table of Contents (15) Chapters Close

Preface 1. Section 1: The Elements of Deep Learning FREE CHAPTER
2. Getting Started with Deep Learning 3. Deep Feedforward Networks 4. Restricted Boltzmann Machines and Autoencoders 5. Section 2: Convolutional Neural Networks
6. CNN Architecture 7. Mobile Neural Networks and CNNs 8. Section 3: Sequence Modeling
9. Recurrent Neural Networks 10. Section 4: Generative Adversarial Networks (GANs)
11. Generative Adversarial Networks 12. Section 5: The Future of Deep Learning and Advanced Artificial Intelligence
13. New Trends of Deep Learning 14. Other Books You May Enjoy

Section 1: The Elements of Deep Learning

In this section, you will get an overview of deep learning with Python, and will also learn about the architectures of the deep feedforward network, the Boltzmann machine, and autoencoders. We will also practice examples based on DFN and applications of the Boltzmann machine and autoencoders, with the concrete examples based on the DL frameworks/libraries with Python, along with their benchmarks.

This section consists of the following chapters:

  • Chapter 1Getting Started with Deep Learning
  • Chapter 2Deep Feedforward Networks
  • Chapter 3Restricted Boltzmann Machines and Autoencoders
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Hands-On Deep Learning Architectures with Python
Published in: Apr 2019
Publisher: Packt
ISBN-13: 9781788998086
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