A content-based recommender system that recommends movies similar to the movie the user likes and analyses the sentiments of the reviews given by the user
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Updated
Jun 9, 2024 - Jupyter Notebook
A content-based recommender system that recommends movies similar to the movie the user likes and analyses the sentiments of the reviews given by the user
The Movie Database for all language movies
Basic Movie Recommendation Web Application using user-item collaborative filtering.
This repository contains the code for building movie recommendation engine.
Movie Recommender System with Django.
Content based movie recommendation system with sentiment analysis
Movie Recommendation System: Project using R and Machine learning
This is a simple movie recommendation modal deployed on Heroku.
It is a movie recommender web application which is developed using the Python.
This is a python project where using Pandas library we will find correlation and give the best recommendation for movies.
Tvflix is a Vanilla JavaScript application that seamlessly retrieves comprehensive movie details using the TMDB API. Discover movies effortlessly with an intuitive search feature, including cast, synopsis, and ratings. Explore personalized movie recommendations based on preferred genres for an enhanced movie-watching journey..
🎥 Movie Recommender AI System
Movie Recommendation System created using Collaborative Filtering (Website) and Content based Filtering (Jupyter Notebook)
Built a movie recommender system with Streamlit and deploy in Heroku Platform.
Movie recommendation system based on hybrid recommender and clustering
Collaborative Filtering Based Movie Recommendation System
A movie recommender system is a system that seeks to predict or filter preferences according to the user's choices. The created Web-App using Python is a similar system, which suggests movies based on the user's liked movies.
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