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.
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Customer ID
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Customer Gender
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Customer Age
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Annual Income of the customer (in Thousand Dollars)
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Spending score of the customer (based on customer behaviour and spending nature)
- Reading the dataset
- EDA
- Finding the k- value by the elbow method
- Using kmeans cluster model
- Visualized the different cluster
