Customer Classification

Overview

This is a simple project on customer classification. This project is an implementation of unsupervised learning. In unsupervised learning the model is not trained on any kind of cleaned and properly classified data. Instead, the model is directly used on the final data and the output is seen. In this problem customers are classified on the basis of their incomes, age, gender etc into different categories. This can be beneficial for the organisation becausr this will help them know what kind of audiance they are targetting which each kind of product and thus they can provide offers and maximise their profit.

Steps followed

Following steps were followed to do this project:

1. Importing data and checking for null values
2. Plotting graphs to find relation among columns
3. Using LabelEncoding on categorical data and then scaling it
4. Using KMeans and Hierarchial Clustering to find optimal number of groups
5. Plot the final graph with all the different classes

Final Classification