Neural Networks

Internal

• Machine Learning

Individual Neuron

Individual neurons are computational units that read input features, represented as an unidimensional vector x1 ... xn in the diagram below, and calculate the hypothesis function as output.

This is a representation of a logistic unit with a sigmoid (logistic) activation function.

The θ vector represents the model's parameters (model's weights). For a multi-layer neural network, the model parameters are collected in matrices named Θ, which will be describe below.

The bias unit is optional, but when it is provided, it is always 1.

Multi-Layer Neural Network

When the output