Topic: user-based-recommendation Goto Github
Some thing interesting about user-based-recommendation
Some thing interesting about user-based-recommendation
user-based-recommendation,A simple movie recommender system that uses two main approaches to make recommendations: Content-based algorithm and Collaborative filtering algorithm (User-based).
User: ahmedshoeb0
user-based-recommendation,Hybrid RecSys, CF-based RecSys, Model-based RecSys, Content-based RecSys, Finding similar items using Jaccard similarity
User: artisan1218
user-based-recommendation,Recommendation System for an Online Beer Company
User: ashutosh27ind
user-based-recommendation,
User: ashwinidprabhu
user-based-recommendation,Association Rule Learning, Content Based Recommendation, Item Based Collaborative, Filtering User Based Collaborative Filtering, Model Based Matrix Factorization projects i've done about
User: atakankizilyuce
user-based-recommendation,Book recommendation system using user base collaborative filter Algorithm and testing the accuracy result by comparing with different algorithms
User: aungkaungpyaepaing
user-based-recommendation,Created Recommender systems using TMDB movie dataset by leveraging the concepts of Content Based Systems and Collaborative Filtering.
User: balajirvp
user-based-recommendation,A hybrid movie recommendation system
User: balaka-18
user-based-recommendation,An Anime Recommendation System based on User-based Collaborative Filtering technique and KNN(Euclidean Distance) algorithm.
User: bislerium
user-based-recommendation,Recommendation algorithms
User: cch230
user-based-recommendation,Game Recommendation using Collaborative filtering with K-Nearest Neighbor
User: ddamddi
user-based-recommendation,Movie Recommendation using Matrix Factorisation, User based collaborative and Item based collaborative filtering
User: divyansha1115
Home Page: https://movie-recomm-1.herokuapp.com/
user-based-recommendation,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.
User: dominic-sagers
user-based-recommendation,Book_Recommendation_Project
User: grknc
user-based-recommendation,Collaborative recommendation engine model for product similarity estimation
User: hjlopes
user-based-recommendation,Books recommendation system by collaborative filtering and certain visualization are done on data.
User: ishtym
user-based-recommendation,Competition for the Recommender Systems course @ PoliMi. The objective is to recommend relevant TV shows to users. Models were evaluated on their MAP@10.
User: jtonglet
user-based-recommendation,An article recommender system for IBM Watson based on User preferences and articles clicked.
User: maazh
user-based-recommendation,Recommendation System for IBM articles
User: marinavillaschi
user-based-recommendation,Sushi Recommender System!
User: matmatromero
user-based-recommendation,Create A Recommendation Engine For Blog Articles
User: maximkiesel1
Home Page: https://www.ibm.com/blogs/watson/
user-based-recommendation,User-based collaborative filtering movie recommender using MovieLens dataset
User: mbodenham
user-based-recommendation,Building a collaborative filtering recommender systems on books dataset
User: mehrabkalantary
user-based-recommendation,Combines user-based and item-based recommendation systems to deliver personalized movie suggestions, utilizing user preferences and film characteristics.
User: mesudepolat
user-based-recommendation,A python implementation of a hybrid semantic-based collaborative filtering recommender systems.
User: noctino52
user-based-recommendation,Cryptocurrency Recommendation based on Tweets
User: petropoulakispanagiotis
user-based-recommendation,A study on the naive user-based collaborative filtering algorithm and related improvements on the Movielens dataset.
User: polaris000
user-based-recommendation,Used User-based and Item-based Collaborative Filtering techniques to build a personalized Book Recommendation System
User: prajaktaghumatkar99
user-based-recommendation,Implementing user-based and item-based collaborative filtering algorithms on MovieLens dataset and comparing the results.
User: pratiknabriya
user-based-recommendation,Demo is available at https://huggingface.co/spaces/quyanh/Book-Recommender-System
User: quyanh2005
Home Page: https://huggingface.co/spaces/quyanh/Book-Recommender-System
user-based-recommendation,An application that recommends music on the basis of previous heard songs of a user using a ML model. Using Collaborative-based filtering to recommend other songs similar to what the user likes. Download Data set from Kaggle (Million song data set)
User: rahulpatil512
user-based-recommendation,Personalised and popularity-based movie recommendations.
User: riakotti
user-based-recommendation,Recommender system for board games built on data collected from major board game forum, BoardGameGeek.
User: richengo
user-based-recommendation,This repo has an implementation of popular recommendation techniques like user-based and item-based collaborative filtering techniques for recommending books and music.
User: ritik872000
user-based-recommendation,Repository of the python scripts for the CS competition held in Kaggle obtaining the 4th place
User: romeomatteo
Home Page: https://inclass.kaggle.com/c/computer-systems-2017-challenge-polimi
user-based-recommendation,This repository contains introductory notebooks for recommendation system.
User: sanketmaneds
user-based-recommendation,Book Recommendation Service
User: sefaoduncuoglu
user-based-recommendation,deep learning project
User: shaghayeghjalali96
Home Page: https://iust-deep-learning.github.io/972/
user-based-recommendation,TMDB_5000_Movie_recommendation_system is a repository for a hybrid movie recommendation system. Discover personalized movie recommendations based on user preferences and movie features using the TMDB 5000 Movies dataset.
User: spoluan
user-based-recommendation,easy use user based collaborative filtering recommender system
User: talhakalem33
user-based-recommendation,Semester project for Tishreen university.
Organization: thekiddos
user-based-recommendation,in this section will be user based recommender on movies and ratings dataset
User: tohid-yousefi
user-based-recommendation, In this section, I will create a user-based recommender on the movie dataset
User: tohid-yousefi
user-based-recommendation,The learning material and projects for the ML algorithms in supervised and unsupervised methods such as Regression, Classification, Clustering and recommender Systems.
User: tyronecheng07
user-based-recommendation,An application that uses the algorithm of user-based collaborative filtering and item-based collaborative filtering to recommend new movies
User: witekha3
user-based-recommendation,Recommender systems
User: y656
user-based-recommendation,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
User: zahradehghanian97
user-based-recommendation,Project of my master thesis (Online Car Recommender system)
User: zawlinucsm
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