Jupyter Notebook · MIT
GokuMohandas/Made-With-ML
Learn how to develop, deploy and iterate on production-grade ML applications.
★ 49.9k
Stars
7.8k forks · 25 open issues
+14/day
Growth · measured
Stars counted between two of our own snapshots roughly a week apart. The repository page gives the exact span.
45.6
Momentum / 100
see the breakdown below
8y ago
Created
last push 8mo ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 22.3 | +14/day, log-scaled against a 750/day ceiling |
| Acceleration | 15 | 9.7 | last week ran 1.64× the monthly pace |
| Freshness | 15 | 0.0 | last push 8mo ago; decays to zero at 180 days |
| Scale | 15 | 13.6 | 49.9k stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 45.6 | sum of the above |
Detail
| Topics | data-engineeringdata-qualitydata-sciencedeep-learningdistributed-mldistributed-trainingllmopsllmsmachine-learningmlopsnatural-language-processingpythonpytorchray |
| Matched on | Data (data-engineering) |
| Short window | +96 stars over 7 days = 13.7/day |
| Long window | +217 stars over 26 days = 8.3/day |
| Lifetime average | 17.09 stars/day over 2,922 days |
| First seen here | 2026-10-11 |
| Last read | 2d ago |