Perceptron & It's Work

What is Perceptron? How it works?

It is an algorithm used for supervised machine learning. It is the building block of Deep Learning. It is a mathematical model.


W1, W2 are the weights and b here refer to the bias

Weights tell us about the feature importance.

bias is provided for increasing model accuracy.

X1 and X2 here are the input features and f is the activation function

Z = W1X1 + W2X2 + b

The summation function Z is passed to the activation function.

The work of the activation is to bring the Z in a range of [-1,1] or [0,1], etc.

Suppose there is a perceptron with a step function as the activation function


Here z = W1X1 + W2X2 + b


Let W1 = A, W2 = B, b = C

X1 = x, X2 = y

So the equation goes by,

Ax + By + C which is a equation of line if we equate with

And interpret with

Ax + By + C >= 0 and

Ax + By + C < = 0

It creates a line in 2D graph and provides the region for classification in it just like,


Perceptron is nothing but a line to create region.

In 3-dimensional feature perceptron becomes a plane.

Perceptron is used in linear or sort of linear

About the Author

Silan Software is one of the India's leading provider of offline & online training for Java, Python, AI (Machine Learning, Deep Learning), Data Science, Software Development & many more emerging Technologies.

We provide Academic Training || Industrial Training || Corporate Training || Internship || Java || Python || AI using Python || Data Science etc