AP

jmschrei/apricot

apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly. See the documentation page: https://apricot-select.readthedocs.io/en/latest/index.html

529 52 +0/wk
GitHub
data-science machine-learning python submodular-optimization submodularity
Trend 3

Star & Fork Trend (16 data points)

Stars
Forks

Multi-Source Signals

Growth Velocity

jmschrei/apricot has +0 stars this period . 7-day velocity: 0.2%.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric apricot gym-starcraft graphbit labnotebook
Stars 529 529529528
Forks 52 13810838
Weekly Growth +0 +0+0+0
Language Jupyter Notebook PythonRustJupyter Notebook
Sources 1 111
License MIT N/AApache-2.0MIT

Capability Radar vs gym-starcraft

apricot
gym-starcraft
Maintenance Activity 22

Last code push 142 days ago.

Community Engagement 49

Fork-to-star ratio: 9.8%. Lower fork ratio may indicate passive usage.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under MIT. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.