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Neural Networks with Keras Cookbook

Neural Networks with Keras Cookbook

By : V Kishore Ayyadevara
3.3 (8)
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Neural Networks with Keras Cookbook

Neural Networks with Keras Cookbook

3.3 (8)
By: V Kishore Ayyadevara

Overview of this book

This book will take you from the basics of neural networks to advanced implementations of architectures using a recipe-based approach. We will learn about how neural networks work and the impact of various hyper parameters on a network's accuracy along with leveraging neural networks for structured and unstructured data. Later, we will learn how to classify and detect objects in images. We will also learn to use transfer learning for multiple applications, including a self-driving car using Convolutional Neural Networks. We will generate images while leveraging GANs and also by performing image encoding. Additionally, we will perform text analysis using word vector based techniques. Later, we will use Recurrent Neural Networks and LSTM to implement chatbot and Machine Translation systems. Finally, you will learn about transcribing images, audio, and generating captions and also use Deep Q-learning to build an agent that plays Space Invaders game. By the end of this book, you will have developed the skills to choose and customize multiple neural network architectures for various deep learning problems you might encounter.
Table of Contents (18 chapters)
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Gender classification of the person in image using the VGG19 architecture-based model

In the previous section, we learned about how VGG16 works. VGG19 is an improved version of VGG16, with a greater number of convolution and pooling operations.

Getting ready

The architecture of the VGG19 model is as follows:

Note that the preceding architecture has more layers, as well as more parameters.

Note that the 16 and 19 in the VGG16 and VGG19 architectures stand for the number of layers in each of these networks. Once we extract the 9 x 9 x 512 output after we pass each image through the VGG19 network, that output will be the input for our model.

Additionally, the process of creating input and output datasets and then building, compiling...

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