Feedforward Neural Network

Training

and

Evaluation.

During the training phase, we take the data set (also called the training set), which includes many pairs of inputs and their corresponding targets (outputs). Our goal is to find a set of weights that would best map the inputs to the desired outputs. In the evaluation phase, we use the network that was created in the training phase, apply our new inputs and expect to obtain the desired outputs.

The training phase will include two steps:

Feedforward

and

Backpropagation

We will repeat these steps as many times as we need until we decide that our system has reached the best set of weights, giving us the best possible outputs.