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Keras Deep Learning Cookbook

You're reading from   Keras Deep Learning Cookbook Over 30 recipes for implementing deep neural networks in Python

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788621755
Length 252 pages
Edition 1st Edition
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Authors (3):
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Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Manpreet Singh Ghotra Manpreet Singh Ghotra
Author Profile Icon Manpreet Singh Ghotra
Manpreet Singh Ghotra
Rajdeep Dua Rajdeep Dua
Author Profile Icon Rajdeep Dua
Rajdeep Dua
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Toc

Table of Contents (12) Chapters Close

Preface 1. Keras Installation 2. Working with Keras Datasets and Models FREE CHAPTER 3. Data Preprocessing, Optimization, and Visualization 4. Classification Using Different Keras Layers 5. Implementing Convolutional Neural Networks 6. Generative Adversarial Networks 7. Recurrent Neural Networks 8. Natural Language Processing Using Keras Models 9. Text Summarization Using Keras Models 10. Reinforcement Learning 11. Other Books You May Enjoy

Sequential models

A Sequential model can be created by passing a stack of layers to the constructor of a class called Sequential. 

How to do it...

Creating a basic Sequential mode involves specifying one or more layers.

Create a Sequential model

We will create a Sequential network with four layers.

  1. Layer 1 is a dense layer which has input_shape of (*, 784) and an output_shape of (*, 32)
A dense layer is a regular densely-connected neural network layer. A Dense layer implements the operation output = activation(dot(input, kernel) + bias), where activation...
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Keras Deep Learning Cookbook
Published in: Oct 2018
Publisher: Packt
ISBN-13: 9781788621755
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