Ecosyste.ms: Repos

An open API service providing repository metadata for many open source software ecosystems.

GitHub topics: recommendation-algorithm

Repositories

simon-muenker/TWON-Ranker

Language: Jupyter Notebook - Size: 179 KB - Last synced: 7 days ago - Pushed: 7 days ago - Stars: 2 - Forks: 1

ssube/feedme

a personalized, offline, imaginary social media feed

Language: Python - Size: 2.5 MB - Last synced: 14 days ago - Pushed: 15 days ago - Stars: 1 - Forks: 1

ztqsteve/Tap-News

A real-time news scraping and recommendation system

Language: Python - Size: 3.08 MB - Last synced: 16 days ago - Pushed: over 5 years ago - Stars: 12 - Forks: 6

tigoCaval/recommendation-algorithm

Collaborative filtering recommendation system. Recommendation algorithm using collaborative filtering. Topics: Ranking algorithm, euclidean distance algorithm, slope one algorithm, filtragem colaborativa.

Language: PHP - Size: 37.1 KB - Last synced: 15 days ago - Pushed: almost 2 years ago - Stars: 74 - Forks: 13

jfkirk/tensorrec

A TensorFlow recommendation algorithm and framework in Python.

Language: Python - Size: 626 KB - Last synced: 18 days ago - Pushed: 12 months ago - Stars: 1,257 - Forks: 223

recommenders-team/recommenders

Best Practices on Recommendation Systems

Language: Python - Size: 210 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 17,902 - Forks: 2,986

Sicmatr1x/EMAN 📦

一个基于SSM框架与物品的协同过滤算法(ItemCF)的简单电子书推荐系统

Language: TSQL - Size: 163 MB - Last synced: 30 days ago - Pushed: almost 4 years ago - Stars: 63 - Forks: 18

morningsky/Torch-RecHub

A Lighting Pytorch Framework for Recommendation System, Easy-to-use and Easy-to-extend.

Language: Python - Size: 24.1 MB - Last synced: 11 days ago - Pushed: almost 2 years ago - Stars: 80 - Forks: 12

cviaai/coronomy

Code the Curve 2020

Language: CSS - Size: 1.66 MB - Last synced: about 2 months ago - Pushed: about 4 years ago - Stars: 2 - Forks: 1

ylongqi/openrec

OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms

Language: Python - Size: 9.77 MB - Last synced: 15 days ago - Pushed: about 1 year ago - Stars: 406 - Forks: 85

recommend-games/board-game-recommender

Board game recommendation engine

Language: Python - Size: 2.26 MB - Last synced: 14 days ago - Pushed: 2 months ago - Stars: 11 - Forks: 0

gasevi/pyreclab

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.

Language: C++ - Size: 1.8 MB - Last synced: 14 days ago - Pushed: over 3 years ago - Stars: 119 - Forks: 29

alperozoner/recommendation_algo_report

An algorithm performance report on the itemKNN algorithm using collaborative filtering paradigm as the learning method. I created this report during my summer internship at B2BPlanet.com

Language: Jupyter Notebook - Size: 2.4 MB - Last synced: 5 months ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

makgyver/pyros

[PY]thon [R]ec[O]mmender [S]ystems library

Language: Python - Size: 55.4 MB - Last synced: 25 days ago - Pushed: over 6 years ago - Stars: 12 - Forks: 6

beomso0/ezSASRec

An easy and efficient tool to build sequential recommendation system utilizing SASRec

Language: Jupyter Notebook - Size: 42.1 MB - Last synced: 13 days ago - Pushed: 7 months ago - Stars: 8 - Forks: 1

qiaoguan/deep-ctr-prediction

CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)

Language: Python - Size: 495 KB - Last synced: 6 months ago - Pushed: over 4 years ago - Stars: 895 - Forks: 275

sharmaroshan/Movie-Recommendation-System

In this Movie Dataset I have used my Basic Knowledge of Recommendation Systems. I have used the Concept of Content -Based Recommendation System to Recommend that If a User Watched a Particular Movie than Which Other Movies He/She is going to like or watch.

Language: Jupyter Notebook - Size: 544 KB - Last synced: 7 months ago - Pushed: about 4 years ago - Stars: 5 - Forks: 2

ozguramac/MITDataScience-CaseStudy4.1

MIT xPRO Data Science Course Movie Recommendations Case Study

Language: Python - Size: 4.56 MB - Last synced: 7 months ago - Pushed: over 6 years ago - Stars: 3 - Forks: 2

daicoolb/PHDMF

This is a new deep learning model for recommender system, which we called PHD

Language: Python - Size: 331 KB - Last synced: 7 months ago - Pushed: over 5 years ago - Stars: 33 - Forks: 12

goldbattle/MangadexRecomendations

Finding recommendations between them all. Work in progress.

Language: Python - Size: 3.94 GB - Last synced: 4 months ago - Pushed: almost 3 years ago - Stars: 19 - Forks: 6

zakaria-narjis/Book-Recommendation-Engine-using-KNN

Book recommendation algorithm using K-Nearest Neighbors

Language: Jupyter Notebook - Size: 24.4 KB - Last synced: 8 months ago - Pushed: over 1 year ago - Stars: 0 - Forks: 1

gbolmier/funk-svd

:zap: A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize

Language: Python - Size: 46.9 KB - Last synced: 6 months ago - Pushed: almost 2 years ago - Stars: 186 - Forks: 57

chihming/competitive-recsys

A collection of resources for Recommender Systems (RecSys)

Size: 77.1 KB - Last synced: 6 months ago - Pushed: over 2 years ago - Stars: 522 - Forks: 116

HowardNTUST/Hackntu2017_demo

This repo is for the demo purpose of Hackntu Data science program.

Language: Python - Size: 3.66 MB - Last synced: 9 months ago - Pushed: almost 6 years ago - Stars: 0 - Forks: 1

arthurkuhn/codejam-2016

Movie Recommendation Engine based on a K-Means clustering algorithm of IMDB public data. Node server for user interface.

Language: Python - Size: 375 KB - Last synced: 10 months ago - Pushed: over 7 years ago - Stars: 2 - Forks: 1

thtang/ML2017FALL

Machine Learning (EE 5184) in NTU

Language: Jupyter Notebook - Size: 684 MB - Last synced: 10 months ago - Pushed: almost 5 years ago - Stars: 67 - Forks: 14

fotol1/RecSysPapersReviews

Size: 816 KB - Last synced: 10 months ago - Pushed: 10 months ago - Stars: 0 - Forks: 0

YuzuruS/redis-recommend

PHP and wrapping Redis's sorted set APIs for specializing recommending operations.

Language: PHP - Size: 30.3 KB - Last synced: 13 days ago - Pushed: over 6 years ago - Stars: 38 - Forks: 6

niharika412/recommendation-dash-app

A book recommendations application that works on the Dash framework and implements content based filtering using TF-IDF and cosine similarity.

Language: Python - Size: 18.4 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 10 - Forks: 5

Yeaseen/ML_Pattern

:trident: Some recognized algorithms[Decision Tree, Adaboost, Perceptron, Clustering, Neural network etc. ] of machine learning and pattern recognition are implemented from scratch using python. Data sets are also included to test the algorithms.

Language: Python - Size: 6.44 MB - Last synced: about 1 year ago - Pushed: about 5 years ago - Stars: 19 - Forks: 3

ys2843/chrome-extension-youtube-controller

Behavior based video recommendation, global keyboard control and ads block for Youtube

Language: JavaScript - Size: 433 KB - Last synced: about 1 year ago - Pushed: about 4 years ago - Stars: 4 - Forks: 0

CAPCOMIN/UprrWebApp

Research on User Profile and Resource Recommendation of Online Learning Platform Based on Collaborative Filtering Algorithm

Language: HTML - Size: 21.9 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 4 - Forks: 1

SebastianMue/JavaRank

Recommendation engine in Java. Based on an ALS algorithm (Apache Spark). Train a new model after N seconds.

Language: Java - Size: 34.2 KB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 13 - Forks: 5

shaped-ai/recsys

Language: Python - Size: 137 KB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 1 - Forks: 0

MartinKondor/MovieRecommender

🎥 Movie Recommender AI System

Language: Jupyter Notebook - Size: 8.03 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 23 - Forks: 6

tlemenestrel/swe_scientific_projects

A collection of scientific projects in C++ and Python

Language: C++ - Size: 6.74 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0

nmrenyi/recommendation-frameworks

Recommendation frameworks for research

Size: 2.93 KB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 1

jingpeicomp/product-relation-mining

商品关联关系挖掘，使用Spring Boot开发框架和Spark MLlib机器学习框架，通过FP-Growth算法，分析用户的购物车商品数据，挖掘商品之间的关联关系。项目对外提供RESTFul接口。

Language: Java - Size: 68.4 KB - Last synced: about 1 year ago - Pushed: almost 3 years ago - Stars: 24 - Forks: 16

TheoLvs/recommendation-systems

Experiments on Recommendation systems

Language: Jupyter Notebook - Size: 1.14 MB - Last synced: about 1 year ago - Pushed: over 5 years ago - Stars: 1 - Forks: 1

berkerol/tum-social-gaming-projects

Projects for Social Gaming course in Technical University of Munich

Language: Jupyter Notebook - Size: 60.2 MB - Last synced: about 1 year ago - Pushed: over 5 years ago - Stars: 3 - Forks: 0

nikolakopoulos/EigenRec

Implementations of the EigenRec algorithm

Language: Fortran - Size: 1.57 MB - Last synced: about 1 year ago - Pushed: over 4 years ago - Stars: 8 - Forks: 2

abdullol/Contextual-Movie-Recommendation-System-Khaana

Contextual Movie Recommender System built on mobile with the aim of showing interest based movies from the huge amount of data based on rating of user and critics which would be crawled from the specified website. Recommender System are primarily directed towards individuals who lack sufﬁcient personal experience or competence to evaluate the potentially overwhelming number of alternative items that a mobile app may offer. We are creating a mobile app based application for contextual recommendation of movies based on Expert Collaborative Filtering [CF]. The application not only recommends movies, but the user can also watch movie show times from cinema relative to recommended movies. The application, however, is much more than yet another implementation of Expert CF. you can offer personalized recommendations on a device with 100% privacy guarantees, but you can also possibly run a recommendation algorithm on the device, with minimum intervention from the server-side. The server is in charge of compiling all the public information available on the mobile app by crawling critic websites like [ Rottentomatoes, IMDB…]. It also gathers information about local cinemas and their schedules. All this information, which again is public, is stored in a SQL database and shared through a RESTful API with devices. The device, connects to the server and syncs a local database through the RESTful API. Once this is done, all needed information is local on the device. Plus... all the personal information about the user (i.e. ratings on movies in this case). The recommendation algorithm can also possibly run locally and return results in a reasonable time because the set of experts is limited. Another important addition to the application is that we have added contextual features. The recommendations you will get on the app can possibly depend on your location. Therefore, it will recommend things that match your taste according to the expert-based prediction but can also be available in a cinema.

Language: Python - Size: 55.4 MB - Last synced: 26 days ago - Pushed: about 1 year ago - Stars: 1 - Forks: 1

vwang0/recommender_system

Recommender system

Language: Jupyter Notebook - Size: 48 MB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 3 - Forks: 0

p0l4r/Matrix-Factorization---based-Collaborative-Filtering

matrix-factorization is a light-weight program written in python language for performing basic operations for matrix factorization-based collaborative filtering. I have plans to create a python module from this repository in the future. If you want to contribute to this project, you are most welcome.

Language: Python - Size: 4.88 KB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 1 - Forks: 0