https://github.com/mayurasandakalum/shop-customer-data-clustering

This notebook provides a comprehensive example of how to perform customer segmentation using K-Means clustering, including data preprocessing, visualization, standardization, one-hot encoding, model training, evaluation, and saving/loading the model.
https://github.com/mayurasandakalum/shop-customer-data-clustering

clustering customer-segmentation kmeans kmeans-clustering machine-learning machinelearning ml segmentation

Last synced: about 2 months ago
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This notebook provides a comprehensive example of how to perform customer segmentation using K-Means clustering, including data preprocessing, visualization, standardization, one-hot encoding, model training, evaluation, and saving/loading the model.

• Host: GitHub
• URL: https://github.com/mayurasandakalum/shop-customer-data-clustering
• Owner: mayurasandakalum
• Created: 2024-06-09T17:41:39.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-06-17T11:11:04.000Z (7 months ago)
• Last Synced: 2024-06-17T13:21:52.811Z (7 months ago)
• Topics: clustering, customer-segmentation, kmeans, kmeans-clustering, machine-learning, machinelearning, ml, segmentation
• Language: Jupyter Notebook
• Homepage:
• Size: 4.85 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:

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