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Python 3.6 下的推荐算法解析，尽量使用简单的语言剖析原理，相似度度量、协同过滤、矩阵分解等
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Summary Of Recommender System Papers | 230 | 5 years ago | ||||||||
| 阅读过的推荐系统论文的归类总结，持续更新中… | ||||||||||
| Recommenderlab | 207 | 8 | 4 | 7 months ago | 24 | September 20, 2023 | 7 | R | ||
| recommenderlab - Lab for Developing and Testing Recommender Algorithms - R package | ||||||||||
| Letterboxd_recommendations | 190 | 3 months ago | 7 | gpl-3.0 | Python | |||||
| Scraping publicly-accessible Letterboxd data and creating a movie recommendation model with it that can generate recommendations when provided with a Letterboxd username | ||||||||||
| Rsparse | 167 | 4 | a year ago | 8 | September 11, 2022 | 6 | R | |||
| Fast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations. | ||||||||||
| Tf Recsys | 76 | 4 years ago | 1 | November 12, 2017 | 1 | mit | Python | |||
| tf-recsys contains collaborative filtering (CF) model based on famous SVD and SVD++ algorithm. Both of them are implemented by tensorflow in order to utilize GPU acceleration. | ||||||||||
| Recommend | 63 | 6 years ago | 1 | Python | ||||||
| Python 3.6 下的推荐算法解析，尽量使用简单的语言剖析原理，相似度度量、协同过滤、矩阵分解等 | ||||||||||
| Reco | 55 | 10 months ago | 12 | March 30, 2020 | 3 | mit | Python | |||
| a simple yet versatile recommendation systems library in python | ||||||||||
| Recommender System | 21 | 7 years ago | Python | |||||||
| In this code we implement and compared Collaborative Filtering algorithm, prediction algorithms such as neighborhood methods, matrix factorization-based ( SVD, PMF, SVD++, NMF), and many others. | ||||||||||
| Collaborative_filtering | 12 | a year ago | Jupyter Notebook | |||||||
| Recommendation system for music. | ||||||||||
| Data Mining | 6 | 5 years ago | n,ull | mit | Python | |||||
| Some Data Mining topics | ||||||||||
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