BOOK_Recommendation_Using_KNN
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Updated
Dec 6, 2020 - Jupyter Notebook
BOOK_Recommendation_Using_KNN
Book recommender api written in flask framework
Stuff of flask project
This is a machine learning project that helps users get book recommendation. The project uses two types of recommendation systems: popularity based to recommend the top 20 books and collaborative filtering to recommend books based on user ratings
This is a book recommendation system using collaborative filtering based on the cosine similarity between user ratings using 'NearestNeighbors' algorithm
This is an end to end book recommendation system.
collaborative filtering
Used Nearest Neighbours to create a book recommendation model
Content-based book recommendation system
Python notebook for Book Recommendation System using collaborative filtering.
Web application which shows Top 50 books of all time & recommends similar books if a book name is provided.
A book recommendation system based on popularity, correlation, and collaborative filtering.
Backend server of FastAPI for recommendation feature
In this project we used a k-nearest neighbors algorithm (KNN) to recommend a book based on your previous book prefrecnces.
This is a fully fledged book shopping webapp including NLP & recommender system
Book Recommendation System - Unsupervised
Book recommendation system using user base collaborative filter Algorithm and testing the accuracy result by comparing with different algorithms
Welcome to our Book Recommendation App Clone! This project brings the magic of personalized book recommendations to your fingertips. Discover your next favorite read with our user-friendly interface and recommendation algorithms. Start exploring the world of literature today!
This repository showcases machine learning projects covering diverse topics such as book recommendations, New York Airbnb analysis, and telecom churn prediction. Each project utilizes various techniques and algorithms to tackle specific challenges and extract meaningful insights from the data.
Add a description, image, and links to the bookrecommendsystem topic page so that developers can more easily learn about it.
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