p768lwy3 / torecsys

ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embedding. The project objective is to develop an ecosystem to experiment, share, reproduce, and deploy in real-world in a smooth and easy way.

Date Created 2019-08-11 (5 years ago)

Commits 210 (last one 2 years ago)

Stargazers 101 (0 this week)

Watchers 5 (0 this week)

Forks 17

License mit

Ranking

RepositoryStats indexes 589,134 repositories, of these p768lwy3/torecsys is ranked #290,247 (51st percentile) for total stargazers, and #333,644 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #53,805/117,584.

p768lwy3/torecsys is also tagged with popular topics, for these it's ranked: python (#12,739/22145), pytorch (#3,561/5977), recommender-system (#150/258), recommendation-system (#71/119)

Other Information

p768lwy3/torecsys has Github issues enabled, there are 3 open issues and 0 closed issues.

Homepage URL: https://pypi.org/project/torecsys/

All Topics

python pytorch embedding-models click-through-rate recommender-system recommendation-system

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updated: 2024-09-12 @ 06:18am, id: 201765888 / R_kgDODAa0AA