We now have everything ready to perform the analysis, except for the engine that will actually attempt to learn the training data.
In this instance, we're going to try to train an artificial neural network to learn the direction of change of the future prices of the input data. In other words, we'll try to train it to tell whether the price will go up or down in the near future. We want to create a simple binary classifier from the past price changes and the text of an article.
As the name implies, artificial neural networks are machine learning structures modeled on the architecture and behavior of neurons, such as the ones found in the human brain. Artificial neural networks come in many forms, but today we're going to use one of the oldest and most common forms: the three-layer feed-forward network.
We can see the structure of a unit outlined in the following figure:
