Movie-Recommender-System is a web application using which a user can select his/her watched movie from list and system will recommend 5 movies to watch according to user interest. For more information about project : Email: [email protected] Python | Streamlit Link: https://movie-recommender-prooject.herokuapp.com/
Collaborative Variational Bandwidth Auto-encoder The codes are associated with the following paper: Collaborative Variational Bandwidth Auto-encoder f
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. QRec has a lightweight architecture and provides user-friendly interfaces. It can facilitate model implementation and evaluation.
🔍 E-Commerce recommender demo 🔍 This is a simple stream setup that uses Memgraph to ingest real-time data from a simulated online store. Data is str
recommender Movies/TV Recommender. Recommends Movies, TV Shows, Actors, Directors, Writers. Setup Create file API_KEY and paste your TMDB API key in i
ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embedding. The project objective is to develop a ecosystem to experiment, share, reproduce, and deploy in real world in a smooth and easy way (Hope it can be done).
recommendersystem Recommendation System to recommend top books from the dataset Introduction The recom.py is the main program code. The dataset is als
This project will access your last listened songs on Spotify using its API, then it will request the user to select 5 favorite songs in that list, on which the API will proceed to make 50 recommendation of songs similar to them.
hang-movie-man Hangman but for movies 😉 This is a fun hangman style game to guess random movie names from the local database and show some summary ab
Movie Pundit Find your next flick by asking the (almost) all-knowing Movie Pundit Jump to Project Source » View Demo · Report Bug · Request Feature Ta
plex-recommender Description: Get movie/tv recommendations based on your current
Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? (SDM 2022) We consider how a user of a web servi
Implementation-of-a-hadoop-based-movie-recommendation-system 通过编写代码，设计一个基于Hadoop的电影推荐系统，通过此推荐系统的编写，掌握在Hadoop平台上的文件操作，数据处理的技能。windows 10 hadoop 2.8.3 p
recommendationsystem matrixfactorization colloborative filtering recommendation
python-recsys A python library for implementing a recommender system. Installation Dependencies python-recsys is build on top of Divisi2, with csc-pys
Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021
GitRec GitRec is the missing recommender system for GitHub repositories based on Gorse. Architecture The trending crawler crawls trending repositories
Fashion-Recommender-System Thr growing e-commerce industry presents us with a la
Explainable Mutual Fund Recommendation Data Please see 'DATA_DESCRIPTION.md' for mode detail. Recommender System Methods Baseline Collabarative Fiilte
Model-Based-Recommender-Engine I created a book Recommender System using Sci-kit learn's N-neighbours algorithm for my model and the streamlit library
plex-recommender Description: Get movie/tv recommendations based on your current
Implementation-of-a-hadoop-based-movie-recommendation-system 通过编写代码，设计一个基于Hadoop的电影推荐系统，通过此推荐系统的编写，掌握在Hadoop平台上的文件操作，数据处理的技能。windows 10 hadoop 2.8.3 p
Included Conferences: SIGIR 2020, SIGKDD 2020, RecSys 2020, CIKM 2020, AAAI 2021, WSDM 2021, WWW 2021
Explainable Mutual Fund Recommendation Data Please see 'DATA_DESCRIPTION.md' for mode detail. Recommender System Methods Baseline Collabarative Fiilte
An implemention of offline RL on recommender system @author: misajie @update: 20
Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various poin
Overview Surprise is a Python scikit for building and analyzing recommender systems that deal with explicit rating data. Surprise was designed with th
This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library (DGL).
RecSim NG, a probabilistic platform for multi-agent recommender systems simulation. RecSimNG is a scalable, modular, differentiable simulator implemented in Edward2 and TensorFlow. It offers: a powerful, general probabilistic programming language for agent-behavior specification;
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.
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