Book Recommendation System built for Book Lovers📖. Simply Rate ⭐ some books and get immediate recommendations🤩

A book recommender system created using simple Restricted Boltzmann Machines in TensorFlow

This repository contains collaborative filtering recommender system build in Python with surprise package to predict book ratings in Book-Crossing dataset.

This is a IBM Watson Based Book Recommendation Chatbot that can recommend the users a specific book depending upon the genre that is provided.

The "Book Recommender System" project aims to provide personalized book recommendations using advanced algorithms and user data. It enhances the reading experience by suggesting books that match users' preferences and interests.

Visit Dr. Libby's clinic and have her prescribe you some books that would do you good. Made with GatsbyJS, Bulma, and Airtable.

A simple books recommender system that provides the functionality to ask for books recommendations or search for them using various options.

NovelNudge is a book recommendation engine that embeds titles, descriptions, authors, and genres using SentenceTransformers. It combines these vectors and ranks similar books with cosine similarity and fuzzy title matching.

Back End Coding for Final Project for "Implementation of Content-Based Filtering on Books Recommendation Application Using Vector Space Model <Case Studi: UMN Library>"

Book Reccomendation System for "Popularity" and "Collaborative Filtraing" Based Reccomendation

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

Recommends books to users depending on their past interest

A framework to ranking information based on user preferences

Book recommendation app using NLP, deployed with Docker, Kubernetes (Kustomize & Helm), and Terraform on GCP.

The "Book Recommender System" project aims to provide personalized book recommendations using advanced algorithms and user data. It enhances the reading experience by suggesting books that match users' preferences and interests.

To develop a Book Recommender System using collaborative filtering with k-NN using a dataset with 278,858 users and 1,149,780 book ratings.

Djangoの公式チュートリアルを参考にして、ログインシステム付き投票システムを作成しました。

This app created using ReactJS recommends a few books across genres to the users.

FCC Projects