neural network

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Introduction

group of interconnected units (neurons) that send signals to one another
units can be either biological cells or mathematical models^[1]
in machine learning, a neural network is an artificial mathematical model used to approximate nonlinear functions
neural networks are usually arranged into layers, with information passing from the input layer through one or more intermediate hidden layers to the final output layer
the input to each unit is a number representing a linear combination of the outputs of the connected neurons in the previous layer
the behavior of the network depends on the strengths of connections between units
a network is trained by modifying these strengths of connections through empirical backpropagation in order to fit some preexisting dataset^[1]
one of the problems of neural networks is over training
- one might think the more the training, the better the fit to the dataset
- not so, comes a point where neural networks trained further deteriorate in performance