A book recommendation system made using item-based collaborative filtering
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Updated
Feb 23, 2024 - Jupyter Notebook
A book recommendation system made using item-based collaborative filtering
This is a Book Recommendation Suite that recommends a book based on the comments/reviews given by the other users, not number of stars, but textual understanding decides the "likability" of a particular book and then matching with the user's liking.
This project is a rest-api that recommend books for user
This project aims to build a Collaborative Filtering-Based Recommender System for suggesting books to users.
A Book Recommendation System based on Collaborative Filtering using Embedding layer to map the ratings given by similar users to the books.
Machine Learning with Python solutions
사용자 선택 기반 도서 추천 웹사이트.
Book Recommendation System
Book recommender command-line application.
In this project, with Pearson correlation, book recommendation algorithm builded to make recommendation between users by their ratings.
Book Recommendation | Collaborative Filtering
A LIMS(library information management system) which recommends book using apriori algorithm.
Movie-Book Cross-Domain Recommender System: Database based application that provides the user with recommendations of movies on the basis of the movies, books and genres explored and rated by him/her
The project utilizes data analysis to recommend books based on user reviews for a given input book. Additionally, it retrieves top-rated books based on customer ratings.
This contains the code of Bharat Book Collection(a dummy book store for project) Back-end.
Bookipedia is a book recommendation project that utilizes neural network embeddings and Wikipedia links to generate personalized book recommendations.
This repository contains the source code of book recommendation system using collaborative filtering. The system recommends the books based on the similarities between user profiles
Book recommendation system through user-based collaborative filtering approach with Java, MySQL, JDBC, Book-Crossing dataset and ICEpdf library
We are proud to introduce our new book recommendation system, book.io. This system uses the user-to-user collaborative filtering model to recommend books to users based on their preferences and ratings.
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