This content-based movie recommender application leverages the Streamlit web framework to provide an intuitive and interactive user interface for recommending movies. The recommendations are generated based on a similarity model trained on data (including cast, crew, story, etc.) of the movies.
- Movie Recommendations: Get personalized movie recommendations based on your selected movie.
- Interactive UI: Easy-to-use interface built with Streamlit.
The dataset used in this project was sourced from Kaggle: TMDB 5000 Movie Dataset.