Concise summary of all major recommender algorithms and concepts
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Updated
Aug 8, 2024
Concise summary of all major recommender algorithms and concepts
Learning Best Practices on Recommender Systems
This repository provides some recommender engine models.
Exploring Machine Learning methods to provide the best recommendation for Expedia
recommender systems algorithms
Link Prediction Recommendation System with Node2Vec
🍪 example for recon-engine
web app in Python using Flask framework
Content Based Movie Recommender
The objective of this project is to build a kNN-based recommender system in order to predict the top 5 movie based on a given movie, in this case "The Post". As there is no need for classification or regression, the nearestNeighbors model and neighrbors() method are used to find the 5 most closely related films.
Recommender engine using SageMaker KMeans clustering for a CloudGuru challenge.
Tell-and-Show is a project for open recommendations that uses the AGPLv3 license to protect *data* and to consider said data as the source for machine learning models.
Multivariate stock price forecasting
Tiktok is an advanced multimedia recommender system that fuses the generative modality-aware collaborative self-augmentation and contrastive cross-modality dependency encoding to achieve superior performance compared to existing state-of-the-art multi-model recommenders.
一个Go语言开发的开源推荐系统, Gorse open source recommender system engine
Pick Me A Flick: A content filtering based Movie Recommendation Engine .
Filters books in lists and shelves, or makes recommendations based on your previous reads.
Incremental recommender engine built with Golang & Redis.
The project develops an application that suggests to the reader more similar articles to that he already read. It uses the embedding algorithms of headlines to create their own numerical representation, which allows to compute the similarity between headlines and get the most similar ones.
A graph-based citation network for paper recommender engine
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