Movie-Match is a smart recommendation engine that leverages Natural Language Processing to understand movie content and suggest similar films. Built with Python and deployed as an interactive web application using Streamlit.
How It Works
- Data Processing: Processes movie metadata including genres, keywords, cast, crew, and overview text
- NLP Vectorization: Converts textual data into numerical vectors using CountVectorizer
- Cosine Similarity: Calculates similarity scores between all movie vectors to find the closest matches
- Interactive UI: Users search for a movie and instantly get personalized recommendations with poster images