花了大概1天的時間整理的各語言的開源推薦系統，比較完整全面的項目標紅。 一、python庫 1、benfred/implicit Fast Python Collaborative Filtering for Implicit Datasets https://github.com/benfred/implicit 2、Mendeley/mrec A recommender systems development and evaluation package by Mendeley https://github.com/mendeley/mrec 3、lyst/lightfm A Python implementation of LightFM, a hybrid recommendation algorithm. https://github.com/lyst/lightfm 4、MrChrisJohnson/logistic-mf Logistic Matrix Factorization for Implicit Feedback Data. https://github.com/MrChrisJohnson/logistic-mf 5、NicolasHug/Surprise A Python scikit for building and analyzing recommender systems https://github.com/NicolasHug/Surprise 6、ocelma/python-recsys A python library for implementing a recommender system https://github.com/ocelma/python-recsys 7、muricoca/crab Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (numpy, scipy, matplotlib). https://github.com/muricoca/crab 8、python-recsys/crab Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (python, numpy, scipy, matplotlib) https://github.com/python-recsys/crab 9、ibayer/fastFM fastFM: A Library for Factorization Machines https://github.com/ibayer/fastFM 10、jadianes/winerama-recommender-tutorial A wine recommender system tutorial using Python technologies such as Django, Pandas, or Scikit-learn, and others such as Bootstrap. https://github.com/jadianes/winerama-recommender-tutorial
二、java庫 1、lenskit/lenskit LensKit recommender toolkit https://github.com/lenskit/lenskit 2、apache/mahout The Apache Mahout project's goal is to build an environment for quickly creating scalable performant machine learning applications. https://github.com/apache/mahout 3、myrrix/myrrix-recommender Stand-alone recommender system from Myrrix https://github.com/myrrix/myrrix-recommender 4、easyrec Add recommendations to your website http://easyrec.org/ 5、SeldonIO/seldon-server Enterprise machine learning platform for prediction and recommendation. https://github.com/SeldonIO/seldon-server 6、rapidminer RapidMiner makes data science teams more productive through a unified platform for data prep, machine learning, and model deployment. https://rapidminer.com/ 7、Duine Framework a Java based recommendation system https://sourceforge.net/projects/duine/ 8、guoguibing/librec LibRec: A Leading Java Library for Recommender Systems https://github.com/guoguibing/librec/ 9、RankSys/RankSys Java 8 Recommender Systems framework for novelty, diversity and much more https://github.com/RankSys/RankSys 10、learning-layers/TagRec Towards A Standardized Tag Recommender Benchmarking Framework https://github.com/learning-layers/TagRec 11、recommenders/rival RiVal recommender system evaluation toolkit https://github.com/recommenders/rival/ 12、OryxProject/oryx Oryx 2: Lambda architecture on Apache Spark, Apache Kafka for real-time large scale machine learning https://github.com/OryxProject/oryx 13、Waikato/moa MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation. https://github.com/Waikato/moa
三、C++庫 1、Gnnng/SVDFeature A recommend system I used before. The official website is http://svdfeature.apexlab.org/wiki/Ma https://github.com/Gnnng/SVDFeature 2、cjlin1/libmf LIBMF is a library for large-scale sparse matrix factorization. For the optimization problem it solves https://github.com/cjlin1/libmf 3、srendle/libfm Library for factorization machines https://github.com/srendle/libfm 4、mikegashler/waffles A toolkit of machine learning algorithms. https://github.com/mikegashler/waffles 5、yixuan/recosystem Recommender System Using Parallel Matrix Factorization https://github.com/yixuan/recosystem
四、其他 1、apache/incubator-predictionio PredictionIO, a machine learning server for developers and ML engineers. Built on Apache Spark, HBase and Spray. https://github.com/apache/incubator-predictionio 2、guymorita/recommendationRaccoon A collaborative filtering based recommendation engine and NPM module built on top of Node.js and Redis. The engine uses the Jaccard coefficient to determine the similarity between users and k-nearest-neighbors to create recommendations. This module is useful for anyone with a database of users, a database of products/movies/items and the desire … https://github.com/guymorita/recommendationRaccoon 3、DataSystemsLab/recdb-postgresql RecDB is a recommendation engine built entirely inside PostgreSQL https://github.com/DataSystemsLab/recdb-postgresql 4、zenogantner/MyMediaLite recommender system library for the CLR (.NET) https://github.com/zenogantner/MyMediaLite 5、crowdrec/idomaar Idomaar is the CrowdRec recommendation and evaluation reference framework. https://github.com/crowdrec/idomaar/ 6、grahamjenson/hapiger HapiGer is an http-wrapper around the Good Enough Recommendation engine using the Hapi.js framework https://github.com/grahamjenson/hapiger 7、OndraFiedler/spark-recommender Scalable recommendation system written in Scala using the Apache Spark framework https://github.com/OndraFiedler/spark-recommender
