GitHub topics: recommendation-algorithm

Repositories

asdhasdasj/Reel-Rec

Reel Rec - A Movie Recommendation AI designed to change the way movie enthusiasts discover and enjoy favorite films. Made using Django & Tailwind CSS.

Size: 1.95 KB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 1 - Forks: 0

klhhrx/Reel-Rec

Reel Rec - A Movie Recommendation AI designed to change the way movie enthusiasts discover and enjoy favorite films. Made using Django & Tailwind CSS.

Size: 1.95 KB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0

andremedina15/Reel-Rec

Reel Rec - A Movie Recommendation AI designed to change the way movie enthusiasts discover and enjoy favorite films. Made using Django & Tailwind CSS.

Size: 1.95 KB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 8 - Forks: 0

recommenders-team/recommenders

Best Practices on Recommendation Systems

Language: Python - Size: 220 MB - Last synced at: 7 days ago - Pushed at: 11 days ago - Stars: 20,291 - Forks: 3,210

twlite/recommendtf

A powerful TensorFlow.js-based collaborative filtering recommendation system

Language: TypeScript - Size: 24.4 KB - Last synced at: 4 days ago - Pushed at: 11 days ago - Stars: 3 - Forks: 0

jfkirk/tensorrec

A TensorFlow recommendation algorithm and framework in Python.

Language: Python - Size: 626 KB - Last synced at: 10 days ago - Pushed at: about 2 years ago - Stars: 1,287 - Forks: 220

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 at: 6 days ago - Pushed at: about 3 years ago - Stars: 84 - Forks: 14

Yonatankinfe/tf-recommender-lightweight-system

A lightweight content-based recommendation system built with Python and TensorFlow/Keras, exposed via a simple REST API with automatic API key generation.

Size: 40 KB - Last synced at: 20 days ago - Pushed at: 22 days ago - Stars: 0 - Forks: 0

ylongqi/openrec

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

Language: Python - Size: 9.77 MB - Last synced at: about 1 month ago - Pushed at: about 2 years ago - Stars: 414 - Forks: 84

songwo-153/Springboot-Smart-Teaching-Recommendation-system

基于Springboot的智慧教学平台的系统设计与实现（智慧教学推荐系统），可以进行学习分析和个性化推荐，系统可以根据学生的学习行为和表现进行分析，生成学习分析报告。根据学生的学习情况和需求，系统可以提供个性化的学习推荐和建议，推荐适合的课程和教学资源推荐（根据用户点击量或浏览量推荐）。

Size: 9.13 MB - Last synced at: about 1 month ago - Pushed at: 7 months ago - Stars: 15 - Forks: 0

thetechleila/Music-Recommendation-Algorithm

A straightforward song recommendation algorithm that utilizes the KMeans Clustering classification method on the "Music Dataset: Lyrics and Metadata from 1950 to 2019"

Language: Jupyter Notebook - Size: 24.9 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

songwo-153/CollaborativeFilteringNewsRecommendSystem

基于协同过滤算法的个性化新闻推荐系统的设计与实现（采用Java语言的SpringBoot和SSM两种框架分别实现基于用户、物品的协同过滤推荐算法）

Size: 7.17 MB - Last synced at: 2 months ago - Pushed at: 4 months ago - Stars: 28 - Forks: 6

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 at: 2 months ago - Pushed at: almost 3 years ago - Stars: 220 - Forks: 67

songwo-153/Collaborative-filtering-music-recommendation-system

基于Springboot协同过滤算法音乐推荐系统开发语言：Java 框架：springboot JDK版本：JDK1.8 服务器：tomcat7 数据库：mysql 5.7 数据库工具：Navicat11 开发软件：idea Maven包：Maven3.3.9 项目介绍: 后端框架使用Springboot+mybatis 前端框架使用Vue 数据库使用mysql 推荐算法使用协同过滤推荐法前台界面采用智能排序向用户进行推荐

Size: 12.3 MB - Last synced at: 2 months ago - Pushed at: 7 months ago - Stars: 4 - Forks: 0

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 at: 8 days ago - Pushed at: about 3 years ago - Stars: 82 - Forks: 13

songwo-153/Fresh-flower-shop-recommendation-system-based-on-collaborative-filtering-algorithm

基于协同过滤算法的鲜花店推荐系统的设计与实现（使用Springboot框架+Mysql数据库+Vue框架+协同过滤算法）,系统分为用户端和管理员端.

Size: 14.6 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 2 - Forks: 0

chihming/competitive-recsys

A collection of resources for Recommender Systems (RecSys)

Size: 77.1 KB - Last synced at: about 2 months ago - Pushed at: over 3 years ago - Stars: 534 - Forks: 115

recommend-games/board-game-recommender

Board game recommendation engine

Language: Python - Size: 2.35 MB - Last synced at: 29 days ago - Pushed at: 6 months ago - Stars: 13 - Forks: 0

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 at: 6 months ago - Pushed at: over 5 years ago - Stars: 920 - Forks: 278

cl-trier/TWON-Ranker

Language: Python - Size: 232 KB - Last synced at: 18 days ago - Pushed at: 10 months ago - Stars: 2 - Forks: 1

goldbattle/MangadexRecomendations

Finding recommendations between them all. Work in progress.

Language: Python - Size: 3.94 GB - Last synced at: about 2 months ago - Pushed at: almost 4 years ago - Stars: 20 - 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 at: 16 days ago - Pushed at: over 1 year ago - Stars: 10 - Forks: 1

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 at: 9 days ago - Pushed at: almost 5 years ago - Stars: 122 - Forks: 28

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 at: about 1 month ago - Pushed at: about 6 years ago - Stars: 23 - Forks: 3

YuzuruS/redis-recommend

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

Language: PHP - Size: 30.3 KB - Last synced at: 7 days ago - Pushed at: over 7 years ago - Stars: 39 - Forks: 6

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 at: 11 months ago - Pushed at: 11 months ago - Stars: 4 - Forks: 1

shahbaz275817/Hotel_finder-graph_based_recommendation_engine

Hotel recommender system on NodeJs and firebase using graph theory

Language: JavaScript - Size: 1.14 MB - Last synced at: 12 months ago - Pushed at: about 6 years ago - Stars: 0 - Forks: 0

weiguanglab/NVIDIA-Merlin-fork Fork of NVIDIA-Merlin/Merlin

This is a fork version of NVIDIA Merlin. NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.

Size: 37 MB - Last synced at: 12 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

ssube/feedme

a personalized, offline, imaginary social media feed

Language: Python - Size: 2.5 MB - Last synced at: about 2 months ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 1

ztqsteve/Tap-News

A real-time news scraping and recommendation system

Language: Python - Size: 3.08 MB - Last synced at: about 1 year ago - Pushed at: over 6 years ago - Stars: 12 - Forks: 6

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 at: about 1 year ago - Pushed at: almost 5 years ago - Stars: 63 - Forks: 18

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 at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

makgyver/pyros

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

Language: Python - Size: 55.4 MB - Last synced at: 22 days ago - Pushed at: over 7 years ago - Stars: 12 - Forks: 6

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 at: over 1 year ago - Pushed at: over 5 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 at: over 1 year ago - Pushed at: over 7 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 at: over 1 year ago - Pushed at: over 6 years ago - Stars: 33 - Forks: 12

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

Book recommendation algorithm using K-Nearest Neighbors

Language: Jupyter Notebook - Size: 24.4 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 1

HowardNTUST/Hackntu2017_demo

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

Language: Python - Size: 3.66 MB - Last synced at: almost 2 years ago - Pushed at: about 7 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 at: almost 2 years ago - Pushed at: over 8 years ago - Stars: 2 - Forks: 1

thtang/ML2017FALL

Machine Learning (EE 5184) in NTU

Language: Jupyter Notebook - Size: 684 MB - Last synced at: almost 2 years ago - Pushed at: almost 6 years ago - Stars: 67 - Forks: 14

fotol1/RecSysPapersReviews

Size: 816 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

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 at: over 2 years ago - Pushed at: over 2 years ago - Stars: 10 - Forks: 5

ys2843/chrome-extension-youtube-controller

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

Language: JavaScript - Size: 433 KB - Last synced at: over 2 years ago - Pushed at: over 5 years ago - Stars: 4 - Forks: 0

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 at: over 2 years ago - Pushed at: over 2 years ago - Stars: 13 - Forks: 5

shaped-ai/recsys

Language: Python - Size: 137 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

MartinKondor/MovieRecommender

🎥 Movie Recommender AI System

Language: Jupyter Notebook - Size: 8.03 MB - Last synced at: over 2 years ago - Pushed at: almost 3 years 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 at: 6 months ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

nmrenyi/recommendation-frameworks

Recommendation frameworks for research

Size: 2.93 KB - Last synced at: over 2 years ago - Pushed at: over 2 years 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 at: over 2 years ago - Pushed at: about 4 years ago - Stars: 24 - Forks: 16

cviaai/coronomy

Code the Curve 2020

Language: CSS - Size: 1.66 MB - Last synced at: 4 months ago - Pushed at: about 5 years ago - Stars: 2 - Forks: 1

TheoLvs/recommendation-systems

Experiments on Recommendation systems

Language: Jupyter Notebook - Size: 1.14 MB - Last synced at: over 2 years ago - Pushed at: over 6 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 at: over 2 years ago - Pushed at: over 6 years ago - Stars: 3 - Forks: 0

nikolakopoulos/EigenRec

Implementations of the EigenRec algorithm

Language: Fortran - Size: 1.57 MB - Last synced at: over 2 years ago - Pushed at: over 5 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 at: about 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 1

vwang0/recommender_system

Recommender system

Language: Jupyter Notebook - Size: 48 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 0

whongyi/post-click-contentRecSys

Code for RecSys'19 paper: Leveraging Post-click Feedback for Content Recommendations

Language: Python - Size: 11.7 KB - Last synced at: 5 months ago - Pushed at: almost 4 years ago - Stars: 15 - Forks: 4

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 at: about 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0