This free podcast describes the concepts of self-interest and competition in a market economy, and their importance as the invisible hand that guides the economy. Branches:
Radial basis function network. In the field of mathematical modeling, a radial basis function network is an artificial neural network that uses radial basis functions as activation functions. The output of the network is a linear combination of radial basis functions of the inputs and neuron parameters. Radial basis function networks have many uses, including function approximation, time series prediction, classification, and system control.
Elusive 'common purpose' sought via national initiative. The architecture of RBF network is a multiplayer feed forward network in which 'n' number of input neurons and 'm' number of output neurons with the hidden layer existing between input and output layer. RBF networks are popular for their fast training and adaptation.