Funk Svd
⚡ A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Recommenderlab | 207 | 8 | 4 | 7 months ago | 24 | September 20, 2023 | 7 | R | ||
| recommenderlab - Lab for Developing and Testing Recommender Algorithms - R package | ||||||||||
| Movielens | 202 | 5 years ago | 5 | mit | Jupyter Notebook | |||||
| 4 different recommendation engines for the MovieLens dataset. | ||||||||||
| Movie_recommend_system | 180 | 2 years ago | mit | Jupyter Notebook | ||||||
| :movie_camera: 一个简单的电影推荐系统 | ||||||||||
| Funk Svd | 154 | 2 years ago | 7 | mit | Python | |||||
| :zap: A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize | ||||||||||
| Pyreclab | 101 | 4 years ago | 9 | March 17, 2021 | 4 | gpl-3.0 | C++ | |||
| pyRecLab is a library for quickly testing and prototyping of traditional recommender system methods, such as User KNN, Item KNN and FunkSVD Collaborative Filtering. It is developed and maintained by Gabriel Sepúlveda and Vicente Domínguez, advised by Prof. Denis Parra, all of them in Computer Science Department at PUC Chile, IA Lab and SocVis Lab. | ||||||||||
| Books2rec | 76 | 5 years ago | 13 | agpl-3.0 | Jupyter Notebook | |||||
| A recommender system built for book lovers. | ||||||||||
| Incrementalsvd.jl | 27 | 4 years ago | 3 | other | Julia | |||||
| Simon Funk's approach to collaborative filtering using the singular value decomposition, implemented in Julia. | ||||||||||
| Recommender_test_bench | 17 | 5 years ago | Python | |||||||
| Recommender system test bench | ||||||||||
| Pysvd | 15 | 11 years ago | Python | |||||||
| CS 324 (Data Mining) final project: efficient regularized SVD/UV-decomposition on large, partial matrices | ||||||||||
| Vr_pca | 7 | 7 years ago | mit | Python | ||||||
| A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate | ||||||||||
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