Class project for UC Berkeley's Master of Information and Data Science Applied Machine Learning course. The project uses a google analytics sample with data on daily online user behaviors to predict user attrition from a service. Attrition will measures in number of days since last session the user is expected to return.
active 2024-07-02 → 2024-08-07 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 37 days from 2024-07-02 to 2024-08-07. Pushes: 27 total, peak 4 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: 2 total, peak 1 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 |
|---|---|---|---|---|
| Mossd-2 | 14 | 14 | 0 | 0 |
| ronghuang0604 | 4 | 4 | 0 | 0 |
| AppleTater | 4 | 4 | 0 | 0 |
| ConorHuh | 3 | 3 | 0 | 0 |
| sacayo | 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 — 2 stars here means stars gained during the window, not the repo's star count.