Neural Network from Scratch

The single-layer Perceptron is the simplest of the artificial neural networks (ANNs). It was developed by American psychologist Frank Rosenblatt in the 1950s. The Perceptron is a linear classifier used for binary predictions. This means that in order for it to work, the data must be linearly separable. Although the Perceptron is only applicable to linearly separable data, the more detailed Multilayered Perceptron can be applied to more complicated nonlinear datasets.