Examples of different types of recommender systems.
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Updated
May 9, 2023 - Jupyter Notebook
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
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
- Collabrative Filtering Based Recomendation System and Popular Filtering based Recommendation System
Recommendation Sytem to Predict Movies using python
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.
Recommend movies to users based on their previous movie ratings Based on previous activities or explicit feedback, content-based filtering recommends other items similar to what the user likes.
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