Problem $1$: Perceptron Learning $(15$ marks$)$

The dataset lab$02\_$dataset$\_1.$csv has a $3-$dimensional input space and a class label of

Positive and Negative. For this task, you are not allowed to use any functionalities of the

sklearn module.

Write a function my$\_$perceptron$()$ which applies perceptron algorithm on the

dataset to create a linear separator. my$\_$perceptron$()$ should return a $3-$dimensional

weight vector which can be used to create the linear separator. Use a classification

threshold of $99\%$ i$.$e$.,$ my$\_$perceptron$()$ will terminate once the misclassification

rate is less than $1\%.(10$ marks$)$

Create a $3$D plot which showcases the dataset in a $3$D$-$space alongwith the linear

separator you obtained from my$\_$perceptron$().$ Use two different colors to represent

the data points belonging in the two classes for ease of viewing. $(5$ marks$)$