Book Image

Deep Learning with Keras

By : Antonio Gulli, Sujit Pal
Book Image

Deep Learning with Keras

By: Antonio Gulli, Sujit Pal

Overview of this book

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of handwritten digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GANs). You will also explore non-traditional uses of neural networks as Style Transfer. Finally, you will look at reinforcement learning and its application to AI game playing, another popular direction of research and application of neural networks.
Table of Contents (16 chapters)
Title Page
About the Authors
About the Reviewer
Customer Feedback


In this chapter, we learned how to use Deep Learning ConvNets for recognizing MNIST handwritten characters with high accuracy. Then we used the CIFAR 10 dataset to build a deep learning classifier in 10 categories, and the ImageNet datasets to build an accurate classifier in 1,000 categories. In addition, we investigated how to use large deep learning networks such as VGG16 and very deep networks such as InceptionV3. The chapter concluded with a discussion on transfer learning in order to adapt pre-built models trained on large datasets so that they can work well on a new domain.

In the next chapter, we will introduce generative adversarial networks used to reproduce synthetic data that looks like data generated by humans; and we will present WaveNet, a deep neural network used for reproducing human voice and musical instruments with high quality.