A content-based movie recommendation system built using metadata from the TMDB 5000 dataset.
It uses NLP techniques (Bag-of-Words + Cosine Similarity) to recommend similar movies based on overview, genre, cast, and keywords.

🌐 Live Demo: streamlit.app

• Search for any movie from the dataset
• Get 5 most similar movies using content-based filtering
• Clean and responsive UI built with Streamlit
• Fast local recommendations (no external APIs used)

• Python
• pandas, scikit-learn
• CountVectorizer (Bag-of-Words)
• Cosine Similarity
• Streamlit for UI

• TMDB 5000 Movies Dataset
  Source: Kaggle

1. Clone the repository:

git clone https://github.com/Zentise/Movie-Recommendation-System.git
cd Movie-Recommendation-System

2. Install requirements:

pip install -r requirements.txt

3. Run the app:

streamlit run streamlit_app.py

Shrijith S Menon
Portfolio: shrijithsm.tech