FilmFinder

A personalized movie recommendation system that provides suggestions based on user preferences and a dataset of movies.

Features

• Leverages ML algorithms to analyze user preferences and suggest movies tailored to individual tastes.
• Integrated into a Streamlit web app, offering an interactive and intuitive platform for easy navigation and usage.
• Provides comprehensive details on recommended movies, including summaries, ratings, genres, and more, to help users make informed viewing choices.
• Utilizes a dataset of over 5,000 movies from TMDB.

Usage

Install required libraries:

pip install -r requirements.txt

Run the application:

streamlit run app.py

Description of various files:

• app.py: Main application for generating movie recommendations.
• requirements.txt: Dependencies for running the project.
• tmdb_5000_movies.csv: Dataset containing movie details.
• tmdb_5000_credits.csv: Dataset containing movie credits.