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

Keras adversarial GANs for forging CIFAR

Now we can use a GAN approach to learn how to forge CIFAR-10 and create synthetic images that look real. Let's see the open source code (  Again, note that it uses the syntax of Keras 1.x, but it also runs on the top of Keras 2.x thanks to a convenient set of utility functions contained in ( First, the open source example imports a number of packages:

import matplotlib as mpl
# This line allows mpl to run with no DISPLAY defined
import pandas as pd
import numpy as np
import os
from keras.layers import Dense, Reshape, Flatten, Dropout, LeakyReLU, 
    Activation, BatchNormalization, SpatialDropout2D
from keras.layers.convolutional import Convolution2D, UpSampling2D, 
    MaxPooling2D, AveragePooling2D
from keras.models import Sequential, Model
from keras...