Customer Segmentation using K-Means & DBSCAN
تفاصيل العمل
Built a customer segmentation model using K-Means and DBSCAN on the Mall Customers dataset, identifying 5 distinct customer groups. Applied data preprocessing and scaling to improve clustering accuracy Created clear visualizations using 2D scatter plots for better insights interpretation Analyzed average spending patterns for each customer segment and delivered actionable insights Used the Elbow Method to determine the optimal number of clusters (K=5) Tools: Python, Pandas, Scikit-learn, Matplotlib, Seaborn Results: Clear separation between clusters + linked each cluster to specific spending behavior
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