Multi-Layer Perceptron using Python

In this tutorial, we will focus on multi-layer perception, it's working, and hands-on in python.

Multi-Layer Perceptron(MLP) is the simplest type of artificial neural network. It is a combination of multiple perceptron models. Perceptrons are inspired by the human brain and try to simulate its functionality to solve problems. In MLP, these perceptrons are highly interconnected and parallel in nature. This parallelization is helpful in faster computation.

Perceptron

Perceptron was introduced by Frank Rosenblatt in 1950. It has the capability to learn complex things just like the human brain. Perceptron network consists of three units: The sensory Unit (Input Unit), Associator Unit (Hidden Unit), and the Response Unit (Output Unit).

How MLP works?

The Perceptron consists of an input layer and an output layer which are fully connected. MLPs have the same input and output layers but may have multiple hidden layers in between as…