Netflix GPT: AI-powered Netflix clone with GPT-based movie recommendations, built with React, Zustand, Firebase, and Vite.
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Updated
Sep 4, 2024 - TypeScript
Netflix GPT: AI-powered Netflix clone with GPT-based movie recommendations, built with React, Zustand, Firebase, and Vite.
This project uses machine learning to create a personalized movie recommendation system. By combining collaborative filtering and content-based filtering, it analyzes user preferences and movie attributes to suggest tailored movie recommendations. The system offers real-time updates and accurate predictions to enhance the user experience.
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.
This Project is meant to give users recommendations of movies to watch on the following basis:
A web application for browsing, reviewing, and rating movies and TV series, built with React, Next.js, and TypeScript. It features user authentication, personalized profiles, and a recommendation system based on user preferences.
Discover your next favorite movie with our personalized recommendation website!
🎬 Movie Search is a movie-recommendation app. You can receive a personalized suggestion based on what you want to watch or assign to a unique roadmap.
Film Finder is a web application that recommends random movies based on genre selection. It uses the TMDB (The Movie Database) API.
Web Application for Movie Reccomendations using FAISS
A movie recommendation system that utilizes FastAPI and Sentence Transformers to suggest films based on plot similarity.
Content based movie recommendation application using content similarity with Flask and OMDb API integration.
A movie search application that allows users to search for movies, displaying details like title, poster, and release year. The app fetches data from the OMDB (Open Movie Database) API.
CineFind is a web application here users can find movies to watch based on genres, streaming services, actors, and more. Users can write reviews, participate in discussions with other users and create lists of their favorite films.
Movie Recommendation System Using Machine Learning
This repository contains the source code for Binge Buddy, a web application that provides personalized movie recommendations based on user preferences and moods. The application uses AI to generate recommendations, allowing users to discover movies that match their interests even if they don't know the specific titles.
MyCinePick is a user-specific movie recommendation system built using collaborative filtering techniques. This project aims to provide personalized movie suggestions tailored to each user's unique viewing preferences and habits.
This project features a Movie Recommendation System that combines cosine similarity for personalized movie suggestions with sentiment analysis of real-time reviews from IMDb. By analyzing user sentiments, the system provides insights into how well-received a movie is by audiences, enhancing the recommendation experience.
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