🎬 Netflix Movie Recommender

Welcome to the Netflix Movie Recommender — a lightweight app that helps you find similar movies based on your favorite pick! Whether you're into thrillers, rom-coms, or mind-bending sci-fi, this app aims to make your next Netflix binge just a click away.

"Built in just 30 minutes during a live demo, but ready to help you all night long."

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💡 About This Project

This project was created during the Google Developer Student Clubs (GDSC) Build with AI event — a dynamic, hands-on session where participants explored the exciting intersection of artificial intelligence and real-world use cases.

I was invited to speak and build a mini AI-powered solution, and in under 30 minutes, we developed a working movie recommendation system using:

• Pandas and scikit-learn for data handling and similarity computation
• Pickle for saving precomputed similarity matrices
• Streamlit for the web interface
• A splash of ✨ enthusiasm + caffeine

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🚀 Try It Live

Click here to test the app:
👉 Netflix Movie Recommender on Streamlit

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🧠 How It Works

1. The app uses a dataset of movies and extracts relevant features like genres, keywords, cast, and crew.
2. It vectorizes this information using TF-IDF and calculates cosine similarity between movies.
3. When a user selects a movie, the app recommends the top 5 most similar titles.

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📦 Tech Stack

• Python
• Pandas, Scikit-learn, Pickle
• Streamlit (for UI)

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🧰 Setup Locally

# Clone the repo
git clone https://github.com/Qudirah/Netflix-movie-recommender.git
cd Netflix-movie-recommender

# Set up virtual env (optional but recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run the app
streamlit run deploy.py