Topic: scikit-surprise Goto Github
Some thing interesting about scikit-surprise
Some thing interesting about scikit-surprise
scikit-surprise,This repo contains my practice and template code for all kinds of recommender systems using SupriseLib. More complex and hybrid Recommender Systems can build on top of these template codes.
User: amanjeetsahu
scikit-surprise,Food Finder: An interface for a multi-user recommendation system.
User: amolratnaparkhe
scikit-surprise,This project is a movie recommender engine written using Python and the Scikit-Surprise libraries to generate better movie recommendations by utilizing temporal user interactiondata.
User: angad-singh97
scikit-surprise,Python Recommendation System
User: chiksumwong
scikit-surprise,The aim of this project is to build a recommendation app. using Collaborative Filtering/ Content based models , scikit-surprise library, Azure function as API and Flask
User: diane-guepet
scikit-surprise,Recommender system that applies a user-to-user collaborative filtering algorithm on the MAL dataset to recommend anime for users.
User: hmc-cs-azhao
scikit-surprise,A Wine Recommender System (My Capstone project for Data Science Immersive course)
User: leewanxian
scikit-surprise,Movie Recommendation using SVD Algorithm
User: ohmdatazwld5
scikit-surprise,Simple Recommender System built using the Scikit Surprise Library. The application provides recommendations based on Amazon Products Reviews.
User: rahulduttt
scikit-surprise,Personalized book recommender system to generate top 5 recommendations to users
User: rakshita95
scikit-surprise,This project aims to build & optimise a book recommendation system based on collaborative filtering and will tackle an example of both memory based & model based approach (using KNNWithMeans & Singular Value Decomposition)
User: rochitasundar
scikit-surprise,Common Machine Learning Examples :computer:
User: ryandsilva
scikit-surprise,A repository containing various projects and microprojects.
User: sheezer
scikit-surprise,Recommend books using various machine learning algorithms.
User: skaty5678
scikit-surprise,A collaborating filtering based system on Movie Lens dataset to recommend user specific movie suggestions. The model was evaluated with recommedation specific metrics including Long Tail plot using 'surprise' library.
User: svpathak
scikit-surprise,RECOMMENDER for films >= 2010. Uses Scikit-Surprise.
User: tamccullough
scikit-surprise,RECOMMENDER for allrecipes.com. Using Scikit-Surprise
User: tamccullough
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