Making a prediction
While this network isn't trained yet, we already can try to make it predict the output of an input, by typing:
propagate(net, [1.0, 2.0, 1.0])
Since the network is initialized with random weights, the output in this case will be a 2-element vector containing gibberish.
Training the network
We can train our network using the dataset we specified earlier:
train!(net, inputs, outputs)
If you need to specify things like the learning rate, momentum rate, number of epochs and batch size, you should check the documentation of the function train!
.