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.
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Updated
Aug 26, 2023
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 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.
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
In this project we used a k-nearest neighbors algorithm (KNN) to recommend a book based on your previous book prefrecnces.
📚A book recommendation and classification system as well as a simple image retrieval system, using the Goodreads dataset.
DL Recommendation System - Book Recommender
Project based on Collaborative filtering using KNN clustering on books dataset, along with Streamlit webapp
Machine Learning Model for recommendation of books using weighted rating and collaborative filtering model.
A book recommendation system based on popularity, correlation, and collaborative filtering.
Used User-based and Item-based Collaborative Filtering techniques to build a personalized Book Recommendation System
Collaborative filtering based book recommendation model deployed using flask
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…
Build a book recommendation system that best predicts the user interests and recommend the suitable books to them, using various approaches.
Content and Collaborative Filtering based book recommendation system
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