🎥 Movie Recommender System

A machine learning-powered system for recommending movies based on user preferences and data analysis. This repository includes both a backend recommendation engine and a frontend interface for user interaction.

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✨ Features

• 🔮 Recommendation Engine: Uses machine learning models to provide personalized movie recommendations.
• 🖥️ Streamlit Application: A user-friendly interface for interacting with the recommendation system.
• 🌐 Frontend: Includes the web-based frontend to provide a better user experience.

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📂 Project Structure

• frontend/ - Frontend application code
• streamlit-app/ - Streamlit application files
• .gitattributes - Git LFS tracking for large files
• Recommendation System.ipynb - Jupyter notebook for the recommendation system
• app.py - Main file for running the application
• dataset.csv - Dataset used for building recommendations
• main.py - Core backend logic
• movies_list.pkl - Serialized movie list (Pickle format)

🛠️ Prerequisites

To run this project, ensure you have the following installed:

• 🐍 Python 3.8+
• 🧰 Streamlit
• 📦 Required Python libraries (listed in requirements.txt)

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🚀 Installation

1. Clone this repository:

   git clone https://github.com/Aymen016/Film-recommendation-engine.git
   cd Film-recommendation-engine

2. Install dependencies:

   pip install -r requirements.txt

3. Set up Git LFS for handling large files (if not already done):

    git lfs install

🏃 Usage

Run the Backend:

Start the backend logic by executing:

python main.py

Run the Streamlit App:

Launch the Streamlit interface:

streamlit run app.py

Access the Frontend:

Use the files in the frontend/ folder to set up and serve the web-based frontend.

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📊 Dataset

• 📁 The dataset (dataset.csv) is used for building movie recommendations.
• 🗂️ movies_list.pkl contains a preprocessed list of movies for faster recommendations.

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🤝 Contributing

Contributions are welcome! Please follow these steps:

1. 🍴 Fork the repository.

2. 🌱 Create a new branch for your feature:

   git checkout -b feature-name

3. ✍️ Commit your changes:

   git commit -m "Add feature-name"

4. 🚀 Push to the branch:

   git push origin feature-name

5. 🛠️ Create a pull request.

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📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

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👨‍💻 About the Author

Aymen Baig
A passionate developer and aspiring Data Scientist specializing in Machine Learning and Natural Language Processing. Experienced in building lightweight and efficient chatbot systems for small businesses. Always open to collaborations and learning new technologies.

• GitHub: Aymen Baig
• LinkedIn: Aymen Baig