ANNs are inspired by the biological neuron with three principal components: 1) dendrites - input connections with other neurons, 2) cell body - the central part of the neuron when the signal is processed, and 3) axons - the output connections to other neurons. ANNs are indeed represented as a set of nodes called neurons and connections between them. The connections have weights and represent their strengths. The basic architecture of a neural network has 3 layers: 1) Input layer - this layer is the interface with the environment; 2) Hidden layer - this is the computational layer; 3) Output layer - this is the layer where the output is stored. Different neural network architecture can be built using multiple layers. In particular, the use of multiple hidden layers could help in solving complex problems. This type of architecture defined the so-called multilayer Feed-Forward networks (see Figure).