figure - simple neural network this network is having an input vector of size hidden layer of size and binary output layer the process of learning an ann will involve the following steps define the structure or architecture of the network we want to use this is critical as if we choose very extensive network containing lot of neurons/units (each circle in figure - can be labeled as neuron or unitthen we can overfit our training data and our model won' generalize well choose the nonlinear transformation to be applied to each connection this transformation controls the activeness of each neuron in the network