This challenge is for an African telecommunications company that provides customers with airtime and mobile data bundles. The objective of this challenge is to develop a machine learning model to predict the likelihood of each customer “churning,” i.e. becoming inactive and not making any transactions for 90 days.
active 2024-04-15 → 2024-05-06 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 22 days from 2024-04-15 to 2024-05-06. Pushes: 23 total, peak 5 in a day. Pull requests: 2 total, peak 2 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 |
|---|---|---|---|---|
| BrianBassey37 | 12 | 12 | 0 | 0 |
| EstherAfari | 6 | 4 | 2 | 0 |
| tirusew-7 | 5 | 5 | 0 | 0 |
| NginaMuinde | 2 | 2 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
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.