Backend for SBAI AI Model using Flask
active 2024-02-04 → 2024-05-11 (UTC)
Complete coverage26,419 / 26,419 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-08-19 (UTC)
Events
46
Pushes
21
Pull requests
1
Issues
12
Stars
1
Forks
0
Activity over time
Daily event counts in the loaded window
Line chart, 98 days from 2024-02-04 to 2024-05-11. Pushes: 21 total, peak 5 in a day. Pull requests: 1 total, peak 1 in a day. Issues: 12 total, peak 3 in a day. Comments: 0 total, peak 0 in a day. Stars: 1 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 |
|---|---|---|---|---|
| JarrettTo | 24 | 13 | 1 | 0 |
| sleep-deepfried | 9 | 7 | 0 | 0 |
| alyannaabalos | 1 | 1 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
- Issue#13JarrettTo2024-03-20 02:47Prediction issue on AWS Instance
- Issue#12JarrettTo2024-03-12 08:25Bug for docker container deployment where training and updating data take forever to load.
- Issue#10JarrettTo2024-02-29 17:48Make date configurable for model predictions
- Issue#9JarrettTo2024-02-29 17:47Figure out why UO prediction is sometimes None
- Issue#8sleep-deepfried2024-02-29 11:39Deployment of the Flask Backend on AWS
- Issue#1JarrettTo2024-02-23 13:21Make Flask server wrapper that can make predictions from the model
- Pull request#7JarrettTo2024-02-23 13:21
- Issue#6JarrettTo2024-02-20 02:12Create similar model for MLB
- Issue#5JarrettTo2024-02-20 02:10Measure accuracy of AI Model on realtime bets
- Issue#4JarrettTo2024-02-20 02:08Add features to the training of NBA Model
- Issue#3sleep-deepfried2024-02-18 15:21Unhandled Runtime Error TypeError: Cannot read properties of undefined (reading 'away_team')
- Issue#2JarrettTo2024-02-10 06:43Make a database platform to store user and prediction data
- Issue#1JarrettTo2024-02-05 17:10Make Flask server wrapper that can make predictions from the model
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 1 stars here means stars gained during the window, not the repo's star count.