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DATA SCIENCE

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Customer segmentation with K-means clustering

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Perform RFM (Recency, Frequency, Monetary) customer segmentation. Process: 1. Calculate RFM scores from transaction data. 2. Normalize features using StandardScaler. 3. Determine optimal K using elbow method and silhouette score. 4. Apply K-means clustering (4-6 segments). 5. Profile each segment with descriptive statistics and business labels (Champions, At-Risk, Lost). Visualize clusters using PCA 2D projection.

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Customer segmentation with K-means clustering

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