perceptron - OpenGenus IQ: Learn Computer Science

Multilayer Perceptron

Multilayer perceptron is a fundamental concept in Machine Learning (ML) that lead to the first successful ML model, Artificial Neural Network (ANN). We have explored the idea of Multilayer Perceptron in depth.

Machine Learning (ML)

When to use Multilayer Perceptrons (MLP)?

Multilayer Perceptrons (MLPs) are the buiding blocks of neural network. They are comprised of one or more layers of neurons. MLPs are used for classification prediction problems, regression prediction problems and tabular datasets.

Machine Learning (ML)

Artificial Neural Networks

An Artificial Neural Network is a form of computing system that vaguely resembles the biological nervous system. It is composed of very many neurons that are centres of computation and learn by a sort of hit and trial method over the course of many epochs. ANN can be seen as a network of perceptrons

Machine Learning (ML)

Perceptron, the building block of modern AI

A perceptron is an artificial neuron that essentially receives input from an input layer, processes the input with the help of an activation function (the Heaviside step function) and gives out the output in the form of either a 0 or 1. The perceptron was invented in 1957 by Frank Rosenblatt