MovieRecommendationUsingML

This Machine learning powered Recommendation Engine suggests Movies for a user based on the user's past intrests by content based filtering. In this ML model the attributes of movies like genres , cast , director , description are taken into consideration while being converted into vector format. The cosine distance is found between the vectors to find the most similar movies based on the user's input . The dataset used is TMDB_5000 Movies dataset. The framework is made using streamlit.

BEFORE RUNNING CODE :

1. EXTRACT contentmodel.zip to same folder
2. COPY contents of datasets to same folder
3. RUN app.py using streamlit to launch the local server