Content and Collaborative Filtering based book recommendation system

A recommendation engine is a class of machine learning which offers relevant suggestions to the customer. A recommendation system is one of the top applications of data science. Every consumer Internet company requires a recommendation system like Netflix, YouTube, a news feed, etc. What you want to show out of a huge range of items is a recomme…

Collaborative filtering based book recommendation model deployed using flask

Machine Learning Model for recommendation of books using weighted rating and collaborative filtering model.

Used User-based and Item-based Collaborative Filtering techniques to build a personalized Book Recommendation System

A book recommendation system based on popularity, correlation, and collaborative filtering.

Build a book recommendation system webapp that best predicts the user interests and recommend the suitable books to them, using various approaches. Python Flask framework is used here.

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

The Book Recommendation System provides personalized book suggestions using Popularity-Based Recommender, Collaborative Filtering, and Cosine Similarity. Implemented with Flask, it allows users to enter a book title and receive tailored recommendations based on their preferences.

This Project Book Recommendation System Develop Using Streamlit and It Contains User-Based Collaborative Filtering & Top Rating of Books.

In this project we used a k-nearest neighbors algorithm (KNN) to recommend a book based on your previous book prefrecnces.

Created a book recommendation system that providing personalized book suggestions based on user ratings and book features. It demonstrates different types of recommendation algorithms and evaluates their performance

This Flask-based Book Recommendation System offers users two main features: a curated list of the top 50 books based on popularity, and personalized book recommendations based on advanced algorithms like Cosine Similarity and Collaborative Filtering. With a simple and intuitive interface.

Build a book recommendation system that best predicts the user interests and recommend the suitable books to them, using various approaches.

A book recommender system using content based filtering

📚A book recommendation and classification system as well as a simple image retrieval system, using the Goodreads dataset.

This is a Basic but Strong Book Recommendation API made with Flask by HIRANMAY ROY using Kaggle Database

Collaborative filter based recommendation system along with user searching pattern.

Comparison of Hybrid Book Recommender Systems: Matrix Factorization with Neural Networks vs. Neural Collaborative Filtering with Attention