Convolution applied to image recognition

In this section, we are now going hands-on by implementing an image recognition model, taking into account the considerations discussed in the first part of this chapter. We are going to implement the same use case using two different frameworks and programming languages.

Keras implementation

The first implementation of object recognition we are going to do is in Python and involves the Keras framework. To train and evaluate the model, we are going to use a public dataset called CIFAR-10 (http://www.cs.toronto.edu/~kriz/cifar.html). It consists of 60,000 (50,000 for training and 10,000 for testing) small (32 x 32 pixels) color images divided into 10 classes (airplane, automobile, bird...