# GavinHacker/recsys\_core

<https://repo.masters-masters.com/en/repos/GavinHacker/recsys_core>

[Home](https://repo.masters-masters.com/en) › [GavinHacker](https://repo.masters-masters.com/en/owners/GavinHacker) › [recsys\_core](https://repo.masters-masters.com/en/repos/GavinHacker/recsys_core)

GavinHacker/recsys\_core has 298 stars on GitHub. Its RepoMasters card: Alpha tier. \[推荐系统\] Based on the scoring data set, the recommendation system is built…

| Field | Value |
| --- | --- |
| Owner | [GavinHacker](https://repo.masters-masters.com/en/owners/GavinHacker) |
| Stars | 298 |
| Forks | 79 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2019 |
| Topics | machine-learning, recommendation-system, logistic-regression, libfm |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [GavinHacker/recsys\_core](https://github.com/GavinHacker/recsys_core) |

## Repository

\[推荐系统\] Based on the scoring data set, the recommendation system is built with FM and LR as the core(基于评分数据集，构建以FM和LR为核心的推荐系统).

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.