This repository contains some of my homework codings of the course "Introduction to Machine learning" in the University of Illinois, Chicago.
Homework 1 Contains code of KNN classifier and its accuracy variations when K is vaired. Homework 2 contains code of Naive Bayes classifier over a spam detection problem Among which it first calculates the classifier accuracy considering all the words in the training data. Secondly it calculates the classifier accuracy considering only the least half of frequent words in the training data Finally it calculates the classifier accuracy considering only the most half of frequent words in the training data. Homework 3 plots a set of points and clusters them using K-Means clustering.