Building a multiclass classifier in Keras

Since we now have a well-defined problem, we can start to code it. As we mentioned earlier, we have to make a few transformations to our inputs and outputs this time. I'll show you those here as we're building the network.

Loading MNIST

Luckily for us, an MNIST loading function that retrieves the MNIST data and loads it for us is built right into Keras. All we need to do is import keras.datasets.mnist and use the load_data() method, as shown in the following code:

(train_X, train_y), (test_X, test_y) = mnist.load_data()

The shape of train_X is 50,000 x 28 x 28. As we explained in the Model inputs and outputs section, we will need to flatten the 28x28 matrix into a 784 element...