🎬 Movie Recommender System

A content-based movie recommendation system built using:

• Python
• Pandas
• Scikit-learn
• Streamlit

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🚀 Live App

👉 Try it here:
https://movie-recommender-ashif.streamlit.app/

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📌 Features

• Recommends 5–10 similar movies
• Content-based filtering (overview, cast, genres, keywords)
• Cosine similarity model
• Clean Streamlit UI
• Deployed on Streamlit Cloud

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🧠 How It Works

1. Movie metadata is processed.
2. Important text features are combined.
3. Text is vectorized using CountVectorizer.
4. Similarity is calculated using cosine similarity.
5. Top similar movies are recommended.

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🛠️ Installation (Run Locally)

Clone the repository:

git clone https://github.com/almdashif/Movie-Recommender.git
cd Movie-Recommender

Create virtual environment:

python -m venv venv
source venv/bin/activate   # Mac/Linux
venv\Scripts\activate      # Windows

Install dependencies:

pip install -r requirements.txt

Run the app:

streamlit run app.py

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📂 Project Structure

Movie-Recommender/
│
├── app.py
├── main.py
├── requirements.txt
├── models/
│   ├── movies.pkl
│   └── similarity.pkl
└── data/

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🌍 Deployment

This app is deployed using Streamlit Community Cloud.

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📧 Author

almdashif