Mall-Customer-Segmentation-Data

This project is part of the Kaggle Mall Customer Segmentation Data competition. K means are used to divide data points into discrete, non-overlapping groupings. One of the most common uses of K means clustering is client segmentation in order to gain a better understanding of them, which can then be used to boost the company's income.

The data includes the following features:

1. Customer ID

2. Customer Gender

3. Customer Age

4. Annual Income of the customer (in Thousand Dollars)

5. Spending score of the customer (based on customer behaviour and spending nature)

Approach:

• Reading the dataset
• EDA
• Finding the k- value by the elbow method
• Using kmeans cluster model
• Visualized the different cluster

dataset

• https://www.kaggle.com/vjchoudhary7/customer-segmentation-tutorial-in-python