A social platform for movie enthusiasts to explore, discuss, and review films. Designed to be your one-stop destination for all movie-related needs, offering a superior user experience and unparalleled depth of content.
RUMORS is a framework designed to implement RESTful APIs for a Recommender System using the MovieLens dataset. The system provides personalized movie recommendations based on user preferences and behavior.
Tvflix is a simple and responsive web app built using Vanilla JS, leveraging the power of Postman and the TMDB API to seamlessly fetch and display comprehensive movie details. This project serves as a template for larger applications.
The 'MOVICO' project is a 'Movie Recommendation System'. It is an 'Artificial Intelligence-Machine Learning' project. Specifically, it is a 'Movie Recommendation System' that uses 'Collaborative Filtering Techniques'. The project 'Movie-Recommendation-System-MOVICO' was created as a project for the course 'Machine Intelligence', 'ue20cs302'.
🎬 FastAPI-based Movie & TV Show Recommender using TMDb API 🎱| Search movies, get recommendations & browse top-rated content!
🎬 It helps you discover films. Search for your favorite movies, get a "Surprise Me" pick, and explore trending movies—all while viewing live details like posters, trailers, ratings, and cast information.
AI powered movie recommendation system using vector search and cosine similarity. The system takes user input in the form of a movie title or overview and returns the most similar movies based on their embeddings.
Movie Visual Features Extracted (MoViFex) dataset web-page
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 Topics
The Movie Recommendation System using KNN (K-Nearest Neighbors) algorithm is a collaborative filtering-based system that suggests movies to users based on similar users' preferences and viewing patterns. The system analyzes user-movie ratings to find users with similar taste patterns and recommends movies that these similar users have enjoyed.
Developed a Movie Recommendation System using content-based filtering and collaborative filtering to suggest personalized movie recommendations.
Recommendo is a movie recommendation system developed using Flask, HTML, Bootstrap, JavaScript, and MySQL. The system allows users to search for movie recommendations and get personalized suggestions based on their favorite movies.
Movie recommendation system using Machine learning
The Movie Information App is a Flutter-based mobile application that provides movie recommendations by utilizing the TMDB (The Movie Database) API. The app allows users to explore movies, view detailed information, and get recommendations based on their interests.
A modern movie recommendation web app built with React, TypeScript, and Material-UI. Discover movies, search by genre, and get details instantly.
This projects serves as a web app to showcase the recommendation engine project
Movie Recommender app created for the course of Human Computer Interaction for Bachelors of Science in Artificial Intelligence from VU Amsterdam
MovieApp is a simple yet powerful movie discovery platform where users can search for movies, browse details, and explore ratings, genres, and release dates. Built with modern web technologies, it ensures a smooth and engaging experience.
Movie96
🎓 🍿 🎬 Final project for the Numerical Analysis for Machine Learning course at Politecnico di Milano.
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