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Facts
| Fact | ahkarami/Deep-Learning-in-Production In this repository, I will share some useful notes and references about deploying deep learning-based models in production. | Tencent/ncnn ncnn is a high-performance neural network inference framework optimized for the mobile platform |
|---|---|---|
| Stars | 4,379 | 24,041 |
| Net stars, last 30 days | +4 | +105 |
| Largest star day | +2 on Sep 29, 2026 | +15 on Jun 30, 2026 |
| Milestone reached in the record | None | None |
| Forks | 684 | 4,547 |
| Language | Not reported | C++ |
| License | No license | Other license |
| Created | May 3, 2018 | Jun 30, 2017 |
| Last push | Nov 9, 2024 | Nov 11, 2026 |
| Archived | No | No |
| Health facts: Maintenance | 1 of 4 checks (2 without data) | 4 of 4 checks |
| Health facts: Releases | 0 of 3 checks (2 without data) | 1 of 3 checks |
| Health facts: Security practice | 0 of 1 check (1 without data) | 0 of 1 check |
| Health facts: Community files | 0 of 3 checks (2 without data) | 2 of 3 checks |
| Commits, last 13 weeks | No data | 158 |
| Weeks with commits, last 52 | No data | 50 of 52 |
| In the Repository Index since | Nov 10, 2026 | Oct 22, 2026 |
Topics that all of them have on the Repository Host: deep-learning, pytorch, keras, mxnet. The facts come from the Repository Host and from the Star History that AwesomeRepos records. A shared topic does not mean that one repository can replace another. Each Health Facts row is one dimension alone. AwesomeRepos does not add them into one score. How each check is defined