This project is about Building a reliable Book Recommendation system through datasets provided,
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Updated
Apr 30, 2023 - Jupyter Notebook
This project is about Building a reliable Book Recommendation system through datasets provided,
😎 This repository contains some recommendation algorithms powered by AI.
Examples of different types of recommender systems.
Books recommendation system based on a hybrid approach of both content-based and collaborative filtering.
I built recommender systems for recommending products to user using Model-based recommendation system.
I created movie recommender system using content based filtering.
Collaborative filtering using SVD
A movie recommendation system, or a movie recommender system, is an ML-based approach to filtering or predicting the users' film preferences based on their past choices and behavior.
Built a movie recommender system using Movielens dataset using both content-based filtering approach and collaborative filtering method.
Movie Recommendation System using the 10M MovieLens dataset
A recommendation engine for an e-commerce website using collaborative filtering
A web app to recommend movies based on user input
book recommendation engine
3rd Year: 1st - 92. A Novel Context Aware Restaurant Recommender System Using Content-Boosted Collaborative Filtering (CACBCF).
Recommend movies to users by review history based on KNN and K-means
Movie Recommendation System is an R project to enhance your Machine Learning knowledge. It is simply a recommendation system that provides consumers with various suggestions based on their history and interests.
MovieLens 100K and MovieLens 1M recommender system
Recommender Systems Project
Demo is available at https://huggingface.co/spaces/quyanh/Book-Recommender-System
A book recommender using content-based filtering on public datasets that suggests similar books to readers based on their interests.
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