user-based-recommendation | Topic

Topic: "user-based-recommendation"

TheKiddos/Restaurant-SyS

Semester project for Tishreen university.

Language: Java - Size: 22.7 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 19 - Forks: 11

mesudepolat/Hybrid-Recommender-System

This project combines user-based and item-based recommendation systems to deliver personalized movie suggestions, utilizing user preferences and film characteristics.

Language: Python - Size: 570 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 11 - Forks: 1

divyansha1115/Movie-recommendation

Movie Recommendation using Matrix Factorisation, User based collaborative and Item based collaborative filtering

Language: JavaScript - Size: 4.33 MB - Last synced at: almost 2 years ago - Pushed at: about 4 years ago - Stars: 7 - Forks: 2

shaghayeghjalali96/movie-recommender-system

deep learning project

Language: Jupyter Notebook - Size: 206 KB - Last synced at: almost 2 years ago - Pushed at: almost 6 years ago - Stars: 7 - Forks: 4

sefaoduncuoglu/book-recommendation-service

Book Recommendation Service

Language: Java - Size: 181 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 6 - Forks: 2

atakankizilyuce/Recommendation-Systems

Association Rule Learning, Content Based Recommendation, Item Based Collaborative, Filtering User Based Collaborative Filtering, Model Based Matrix Factorization projects i've done about

Language: Python - Size: 25.4 KB - Last synced at: 11 months ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 0

mbodenham/k-nn-movie-recommender

User-based collaborative filtering movie recommender using MovieLens dataset

Language: Python - Size: 45.9 KB - Last synced at: 8 months ago - Pushed at: about 5 years ago - Stars: 5 - Forks: 1

hjlopes/collaborative-filtering

Collaborative recommendation engine model for product similarity estimation

Language: Jupyter Notebook - Size: 106 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 1

IshtyM/Books-Recommender-System-

Books recommendation system by collaborative filtering and certain visualization are done on data.

Language: Jupyter Notebook - Size: 2.88 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 0

artisan1218/Recommendation-System

Hybrid RecSys, CF-based RecSys, Model-based RecSys, Content-based RecSys, Finding similar items using Jaccard similarity

Language: Python - Size: 63 MB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 4 - Forks: 1

pratiknabriya/Recommender-System-Collaborative-Filtering-MovieLens

Implementing user-based and item-based collaborative filtering algorithms on MovieLens dataset and comparing the results.

Language: Jupyter Notebook - Size: 835 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 4

alejandro-yakovlev/cf-php

This library is a PHP implementation of the collaborative filtering (CF).

Language: PHP - Size: 34.2 KB - Last synced at: 17 days ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

Balajirvp/Recommender-Systems---Content-Based-Systems-and-Collaborative-Filtering

Created Recommender systems using TMDB movie dataset by leveraging the concepts of Content Based Systems and Collaborative Filtering.

Language: Jupyter Notebook - Size: 1.54 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

grknc/NeOkusam-Book-Recommendation-Project

Book_Recommendation_Project

Language: Jupyter Notebook - Size: 5.99 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

AshwiniDPrabhu/Music-Recommender-System

Language: HTML - Size: 1.15 MB - Last synced at: 5 months ago - Pushed at: over 5 years ago - Stars: 2 - Forks: 2

talhakalem33/User-Based-Collaborative-Filtering-Recommender-System

easy use user based collaborative filtering recommender system

Language: Python - Size: 15.6 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

cch230/Recommendation-Algorithm

Recommendation algorithms

Language: Python - Size: 1.75 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

aungkaungpyaepaing/Book-Recommendation-System

Book recommendation system using user base collaborative filter Algorithm and testing the accuracy result by comparing with different algorithms

Language: Jupyter Notebook - Size: 331 KB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Mehrab-Kalantari/Book-Recommender-System

Building a collaborative filtering recommender systems on books dataset

Language: Jupyter Notebook - Size: 2.39 MB - Last synced at: 2 months ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

ArazShilabin/movie-recommender-system

Language: Python - Size: 222 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

matmatromero/sushi

Sushi Recommender System!

Language: Jupyter Notebook - Size: 1.17 MB - Last synced at: 12 days ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0

AhmedShoeb0/MovieRecommenderSystem

A simple movie recommender system that uses two main approaches to make recommendations: Content-based algorithm and Collaborative filtering algorithm (User-based).

Language: Python - Size: 14.3 MB - Last synced at: 10 months ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0

zahraDehghanian97/Matrix-Factorization-recommender-System

In this repository, I implement a recommender system using matrix factorization. Here, two types of RS are implemented. First, use the factorized matrix for user and item. and second, rebuild the Adjacency matrix. both approaches are acceptable and implemented in this repo. To factorized the matrix, funk-svd Algorithm is used. you can find his implementation on this link: https://github.com/gbolmier/funk-svd

Language: Python - Size: 18.2 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

PetropoulakisPanagiotis/cryptocurrencyRecommendation

Cryptocurrency Recommendation based on Tweets

Language: C++ - Size: 15.1 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

Polaris000/MovieRecommendationSystem

A study on the naive user-based collaborative filtering algorithm and related improvements on the Movielens dataset.

Language: Python - Size: 2.56 MB - Last synced at: 3 months ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

maazh/ibm-watson-recommender-system

An article recommender system for IBM Watson based on User preferences and articles clicked.

Language: Jupyter Notebook - Size: 4.99 MB - Last synced at: about 2 years ago - Pushed at: almost 6 years ago - Stars: 1 - Forks: 0

sumit1202/recflix Fork of AndyPSam/recflix

Language: JavaScript - Size: 9.55 MB - Last synced at: about 1 year ago - Pushed at: about 7 years ago - Stars: 1 - Forks: 0

eylulozatman/bookRecSystemSurprise

collaborative filtering project was developed using surprise library. It provides user based and item based search. It calculates similarity score and offers suggestions.

Language: Python - Size: 4.03 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

pylena/Cafe-Analysis

Analysis of Blooming Cafe Sales

Language: Jupyter Notebook - Size: 1.83 MB - Last synced at: about 2 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

deliprofesor/Cinematic-Data-Analytics-and-Recommendation-Platform

This project analyzes a movie dataset using machine learning algorithms to predict success, explore revenue-popularity relationships, and develop recommendation systems. It employs techniques like K-Means, DBSCAN, GMM, decision trees, PCA, and NLP for insights and personalized suggestions.

Language: Python - Size: 1.83 MB - Last synced at: about 1 month ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

FoggySmile/RecSys

RecSys

Language: Jupyter Notebook - Size: 199 KB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

jtonglet/Recommender-Systems-Polimi

Competition for the Recommender Systems course @ PoliMi. The objective is to recommend relevant TV shows to users. Models were evaluated on their MAP@10.

Language: Python - Size: 16.7 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 1

Roshni-Bala/Product-Recommendation-System

Recommendation System for Appliances, along with Topic Modelling and Sentiment Analysis

Language: Jupyter Notebook - Size: 8.54 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

dominic-sagers/MovieLens-20M-Recommender-System

Using the MovieLens 20 Million review dataset, this project aims to explore different ways to design, evaluate, and explain recommender systems algorithms. Different item-based and user-based recommender systems are showcased as well as a hybrid algorithm using a modified page-rank algorithm.

Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0