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GitHub topics: cluster-profiling

Leox2f/credit_card_customer_segmentation

Customer segmentation analysis on credit card users to identify distinct customer groups based on their behavior and characteristics. The analysis uses unsupervised machine learning techniques, specifically K-means clustering, to group customers into meaningful segments.

Language: Jupyter Notebook - Size: 1.1 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

dpruthardt/UnsupervisedLearning

Language: HTML - Size: 3.46 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

hugohiraoka/Credit_Card_Customer_Segmentation

Classification Model of Potential Credit Card Customers

Language: HTML - Size: 12.7 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Pratyush1296/Clustering-Comparison-between-methods

Language: R - Size: 1000 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

alef-s/Trade_Ahead_Unsupervised_Learning

Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.

Size: 1.17 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

S-CHAN11/Bank-Customer-Segmentation

The objective of this project is to analyze the customers of a bank, categorize them with K-Means and Hierarchical Clustering and evaluate their distinct characteristics

Language: Jupyter Notebook - Size: 3.21 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

Yemi-Ak/Unsupervised-Learning-Trade-Ahead

Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.

Language: Jupyter Notebook - Size: 2.36 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0