This project segments customers based on their purchasing behavior using K-Means clustering. The dataset includes age, annual income, and spending score. The Elbow Method determines the optimal clusters, and PCA helps visualize them. Key insights guide businesses in targeting high-value customers and optimizing marketing strategies.
active 2025-03-02 → 2025-03-02 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2025-03-02 to 2025-03-02. Pushes: 2 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| abujabarmubarak | 2 | 2 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.