recommenderNReco Recommender is a .NET port of Apache Mahout CF java engine (standalone, non-Hadoop version)
Stars: ✭ 35 (-66.98%)
Mutual labels: collaborative-filtering, recommender, recommendation-system, recommendation-engine, recommender-system
CornacA Comparative Framework for Multimodal Recommender Systems
Stars: ✭ 308 (+190.57%)
Mutual labels: collaborative-filtering, matrix-factorization, recommendation-system, recommendation-engine, recommender-system
retailbox🛍️RetailBox - eCommerce Recommender System using Machine Learning
Stars: ✭ 32 (-69.81%)
Mutual labels: matrix-factorization, recommendation-system, recommendation-engine, recommender-system
Movie Recommender SystemBasic Movie Recommendation Web Application using user-item collaborative filtering.
Stars: ✭ 85 (-19.81%)
Mutual labels: collaborative-filtering, recommendation-system, recommendation-engine, recommender-system
Recsys2019 deeplearning evaluationThis is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
Stars: ✭ 780 (+635.85%)
Mutual labels: collaborative-filtering, matrix-factorization, recommendation-system, recommender-system
Awesome-Machine-Learning-Papers📖Notes and remarks on Machine Learning related papers
Stars: ✭ 35 (-66.98%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender-system
LibrecLibRec: A Leading Java Library for Recommender Systems, see
Stars: ✭ 3,045 (+2772.64%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender
Recommendation.jlBuilding recommender systems in Julia
Stars: ✭ 42 (-60.38%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender-system
Recommendation-System-BaselineSome common recommendation system baseline, with description and link.
Stars: ✭ 34 (-67.92%)
Mutual labels: collaborative-filtering, matrix-factorization, recommendation-system
DeeprecAn Open-source Toolkit for Deep Learning based Recommendation with Tensorflow.
Stars: ✭ 954 (+800%)
Mutual labels: collaborative-filtering, matrix-factorization, recommendation-system
RecoderLarge scale training of factorization models for Collaborative Filtering with PyTorch
Stars: ✭ 46 (-56.6%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender-system
Rectorchrectorch is a pytorch-based framework for state-of-the-art top-N recommendation
Stars: ✭ 121 (+14.15%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender-system
RsparseFast and accurate machine learning on sparse matrices - matrix factorizations, regression, classification, top-N recommendations.
Stars: ✭ 145 (+36.79%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender-system
DaisyrecA developing recommender system in pytorch. Algorithm: KNN, LFM, SLIM, NeuMF, FM, DeepFM, VAE and so on, which aims to fair comparison for recommender system benchmarks
Stars: ✭ 280 (+164.15%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender-system
TIFUKNNkNN-based next-basket recommendation
Stars: ✭ 38 (-64.15%)
Mutual labels: collaborative-filtering, recommendation-system, recommender-system
PolaraRecommender system and evaluation framework for top-n recommendations tasks that respects polarity of feedbacks. Fast, flexible and easy to use. Written in python, boosted by scientific python stack.
Stars: ✭ 205 (+93.4%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender-system
LightfmA Python implementation of LightFM, a hybrid recommendation algorithm.
Stars: ✭ 3,884 (+3564.15%)
Mutual labels: matrix-factorization, recommender, recommender-system
CarskitJava-Based Context-aware Recommendation Library
Stars: ✭ 98 (-7.55%)
Mutual labels: matrix-factorization, recommendation-engine, recommender-system
ElliotComprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
Stars: ✭ 49 (-53.77%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender-system
ImplicitFast Python Collaborative Filtering for Implicit Feedback Datasets
Stars: ✭ 2,569 (+2323.58%)
Mutual labels: collaborative-filtering, matrix-factorization, recommender-system