開源推薦系統整理

阿新 • • 發佈：2019-01-06

花了大概1天的時間整理的各語言的開源推薦系統，比較完整全面的專案標紅。 一、python庫 1、benfred/implicit Fast Python Collaborative Filtering for Implicit Datasets 2、Mendeley/mrec A recommender systems development and evaluation package by Mendeley 3、lyst/lightfm A Python implementation of LightFM, a hybrid recommendation algorithm. 4、MrChrisJohnson/logistic-mf

Logistic Matrix Factorization for Implicit Feedback Data. 5、NicolasHug/Surprise A Python scikit for building and analyzing recommender systems 6、ocelma/python-recsys A python library for implementing a recommender system 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).

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) 9、ibayer/fastFM fastFM: A Library for Factorization Machines 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. 二、java庫 1、lenskit/lenskit LensKit recommender toolkit 2、apache/mahout The Apache Mahout™ project's goal is to build an environment for quickly creating scalable performant machine learning applications. 3、myrrix/myrrix-recommender Stand-alone recommender system from Myrrix 4、easyrec Add recommendations to your website 5、SeldonIO/seldon-server Enterprise machine learning platform for prediction and recommendation. 6、rapidminer RapidMiner makes data science teams more productive through a unified platform for data prep, machine learning, and model deployment. 7、Duine Framework a Java based recommendation system 8、guoguibing/librec LibRec: A Leading Java Library for Recommender Systems 9、RankSys/RankSys Java 8 Recommender Systems framework for novelty, diversity and much more 10、learning-layers/TagRec Towards A Standardized Tag Recommender Benchmarking Framework 11、recommenders/rival RiVal recommender system evaluation toolkit 12、OryxProject/oryx Oryx 2: Lambda architecture on Apache Spark, Apache Kafka for real-time large scale machine learning 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. 三、C++庫 1、Gnnng/SVDFeature 2、cjlin1/libmf LIBMF is a library for large-scale sparse matrix factorization. For the optimization problem it solves 3、srendle/libfm Library for factorization machines 4、mikegashler/waffles A toolkit of machine learning algorithms. 5、yixuan/recosystem Recommender System Using Parallel Matrix Factorization 四、其他 1、apache/incubator-predictionio PredictionIO, a machine learning server for developers and ML engineers. Built on Apache Spark, HBase and Spray. 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 … 3、DataSystemsLab/recdb-postgresql RecDB is a recommendation engine built entirely inside PostgreSQL 4、zenogantner/MyMediaLite recommender system library for the CLR (.NET) 5、crowdrec/idomaar Idomaar is the CrowdRec recommendation and evaluation reference framework. 6、grahamjenson/hapiger HapiGer is an http-wrapper around the Good Enough Recommendation engine using the Hapi.js framework 7、OndraFiedler/spark-recommender Scalable recommendation system written in Scala using the Apache Spark framework

開源推薦系統整理

開源推薦系統整理

開源推薦系統Librec中recommender模組演算法瞭解——cf模組

16個推薦系統開放公共資料集整理分享

推薦系統學習之評測指標

推薦系統之冷啟動問題

個性化推薦系統原理介紹（基於內容過濾／協同過濾／關聯規則／序列模式）

推薦系統相關算法

推薦系統評測指標—準確率(Precision)、召回率(Recall)、F值(F-Measure)

【推薦系統實戰】：C++實現基於用戶的協同過濾（UserCollaborativeFilter）

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機器人--推薦系統

.net開源項目整理

第一篇：你不一定了解的"推薦系統"

隨時更新———個人喜歡的關於模式識別、機器學習、推薦系統、圖像特征、深度學習、數值計算、目標跟蹤等方面個人主頁及博客

linux acl訪問控制列表系統整理

下載基於大數據技術推薦系統實戰教程(Spark ML Spark Streaming Kafka Hadoop Mahout Flume Sqoop Redis)

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推薦系統

推薦系統(recommender systems):預測電影評分--構造推薦系統的一種方法：協同過濾(collaborative filtering )

開源推薦系統整理

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