Movies/TV Recommender.
Recommends Movies, TV Shows, Actors, Directors, Writers.
Create file API_KEY and paste your TMDB API key in it.
Install requirements:
pip install requirements.txt
streamlit run recommender.py
recommender Movies/TV Recommender. Recommends Movies, TV Shows, Actors, Directors, Writers. Setup Create file API_KEY and paste your TMDB API key in i
COTREC Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'. Requirements: Python 3.7, Pytorch 1.6.0 Best Hype
QRec is a Python framework for recommender systems (Supported by Python 3.7.4 and Tensorflow 1.14+) in which a number of influential and newly state-of-the-art recommendation models are implemented.
This project is based on cloud services to create data lake, ETL process, train and deploy learning model to implement a recommendation system.
Recommender systems are the systems that are designed to recommend things to the user based on many different factors. The recommender system deals with a large volume of information present by filte
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KCGN AAAI-2021 《Knowledge-aware Coupled Graph Neural Network for Social Recommendation》 Environments python 3.8 pytorch-1.6 DGL 0.5.3 (https://github.
(中文文档|简体中文|English) 什么是推荐系统? 推荐系统是在互联网信息爆炸式增长的时代背景下，帮助用户高效获得感兴趣信息的关键； 推荐系统也是帮助产品最大限度吸引用户、留存用户、增加用户粘性、提高用户转化率的银弹。 有无数优秀的产品依靠用户可感知的推荐系统建立了良好的口碑，也有无数的公司依
Annoy Annoy (Approximate Nearest Neighbors Oh Yeah) is a C++ library with Python bindings to search for points in space that are close to a given quer
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exemplo-de-sistema-especialista EXEMPLO DE SISTEMA ESPECIALISTA PARA RECOMENDAR SERIADOS EM PYTHON Resumo O objetivo de auxiliar o usuário na escolha
FairGo WWW2021 Learning Fair Representations for Recommendation: A Graph-based Perspective As a key application of artificial intelligence, recommende
MusicPlayer 基于个性化推荐的音乐播放系统 Hi, 这是我在大四的时候做的毕设，现如今将该项目开源。 本项目是基于Python的tkinter和pygame所著。 该项目总体来说，代码比较烂（因为当时水平很菜）。 运行的话安装几个基本库就能跑，只不过里面的数据还没有上传至Github。 先
Introduction This is the repository of our accepted CIKM 2021 paper "Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Trans
MKM-SR Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation Paper data and code This is the
Recommendation engines are one of the most well known, widely used and highest value use cases for applying machine learning. Despite this, while there are many resources available for the basics of
SEFrame This repository contains the code for the paper "An Efficient and Effective Framework for Session-based Social Recommendation". Requirements P
Overview Surprise is a Python scikit for building and analyzing recommender systems that deal with explicit rating data. Surprise was designed with th
Movie-Recommender-System Movie-Recommender-System is a web application using which a user can select his/her watched movie from list and system will r
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