K-means is one of the most widely used unsupervised learning algorithms that solve well-known clustering problems. The procedure follows a simple and easy way to classify a given data set through "k" clusters.
The main idea is to define k centers, one for each cluster. These centers should be placed systematically since different locations causes different results.
In this assignment, a custom dataset was generated by using a third-party library.