# jmschrei/apricot

<https://repo.masters-masters.com/en/repos/jmschrei/apricot>

[Home](https://repo.masters-masters.com/en) › [jmschrei](https://repo.masters-masters.com/en/owners/jmschrei) › [apricot](https://repo.masters-masters.com/en/repos/jmschrei/apricot)

jmschrei/apricot has 537 stars on GitHub. Its RepoMasters card: Alpha tier. apricot implements submodular optimization for the purpose of selecting subsets of…

| Field | Value |
| --- | --- |
| Owner | [jmschrei](https://repo.masters-masters.com/en/owners/jmschrei) |
| Stars | 537 |
| Forks | 53 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2018 |
| Topics | python, submodular-optimization, submodularity, data-science, machine-learning |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [jmschrei/apricot](https://github.com/jmschrei/apricot) |

## Repository

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

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.