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

Movie Recommendation System using Collaborative Method (User - User similarity , Item-Item similarity)

book recommendation engine

MovieLens 100K and MovieLens 1M recommender system

Recommender Systems Project

Demo is available at https://huggingface.co/spaces/quyanh/Book-Recommender-System

Recommendation Sytem to Predict Movies using python

- Collabrative Filtering Based Recomendation System and Popular Filtering based Recommendation System

Versão final do recommender desenvolvido no DEX4 da DNC

Neural matrix factorization movie recommender paired with image similarity in poster design

This project implements a magazine recommender system using Amazon review data from 2018 . The system calculates similarity scores between magazines and recommends the most similar magazines to the user.

Simple and user-friendly Python package for building recommendation systems based on PMF.

This project is a Recommendation based project. Similar movies will be recommended based upon the content of the movie. I have used ML algorithm & BOW technique of NLP for our model. An interactive web page is also designed using streamlit library for next level user experience.