Netflix GPT: AI-powered Netflix clone with GPT-based movie recommendations, built with React, Zustand, Firebase, and Vite.

Movie trailer streaming app.

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.

Pick 3 Movies, and Let Us Find Your Next Must-Watch!

Explore new movies , Rate them & add it to your List. You can also rate your favorite movie and add the movie to your own personalised list. The data of the list will also be stored in your browser so it is a complete app.

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.

Movie Recommendation System A TF-IDF based movie recommendation system that suggests movies based on your preferences. With a database of 10,000 movies, this system is designed to enhance your movie-watching experience by recommending films similar to the ones you've enjoyed.

This Project is meant to give users recommendations of movies to watch on the following basis:

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.

A movie recommendation app that is used together with Gemini and pathway.

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!

An ML-based movie recommendation system built using a dataset from Kaggle. This project preprocesses movie data to generate recommendations based on cosine similarity. The system uses Python libraries such as Pandas, NumPy, NLTK, and sklearn for data processing and machine learning. The user interface is developed with Streamlit.

A dynamic website that provides real-time rankings of the best movies, allowing users to see up-to-date information on top-rated films. The site integrates with a public API to fetch movie data and updates the rankings continuously based on user ratings and reviews.

🎬 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.

IMDb Data Dashboard