Practical Convolutional Neural Networks

Handwritten number recognition with Keras and MNIST

A typical neural network for a digit recognizer may have 784 input pixels connected to 1,000 neurons in the hidden layer, which in turn connects to 10 output targets — one for each digit. Each layer is fully connected to the layer above. A graphical representation of this network is shown as follows, where x are the inputs, h are the hidden neurons, and y are the output class variables:

In this notebook, we will build a neural network that will recognize handwritten numbers from 0-9.

The type of neural network that we are building is used in a number of real-world applications, such as recognizing ...