In this post, we are going to have a look at a program written in Python3 using numpy. We will discuss the basics of what a **perceptron **is, what is the **delta rule **and how to use it to converge the learning of the perceptron.

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What is a perceptron?

The perceptron is an algorithm for supervised learning of binary classifiers (let’s assumer {1, 0}). We have a linear combination of weight vector and the input data vector that is passed through an activation function and then compared to a threshold value. If the linear combination is greater than the threshold, we predict the class as 1 otherwise 0\. Mathematically,

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