Just as there are many different types of learning and approaches to human learning, so we can say about the machines as well. To ensure that a machine will be able to learn from experience, it is important to define the best available methodologies depending on the specific job requirements. This often means choosing techniques that work for the present case and evaluating them from time to time, to determine if we need to try something new.
 We have seen the basics of neural networks in Chapter 1, Neural Network and Artificial Intelligence Concepts, and also two simple implementations using R. In this chapter, we will deal with the learning process, that is how to train, test, and deploy a neural network machine learning model. The training phase is used for learning, to fit the parameters of the neural networks. The testing phase is...
