This Movie Recommendation System is a web application built using Django that provides personalized movie recommendations to users based on their preferences and viewing history. The recommendations are generated using machine learning algorithms to enhance the user experience.
- User Registration and Authentication: Users can create accounts and log in to the system.
- Movie Database: A comprehensive database of movies with details such as title, genre, and user ratings.
- User Profile: Users can set their preferences, rate movies, and view their viewing history.
- Recommendation Engine: Utilizes machine learning algorithms to generate movie recommendations for users.
- Search Functionality: Users can search for movies by title, genre, or other criteria.
- Responsive Design: The system is responsive, ensuring a seamless user experience on various devices.
- Python 3.x
- Django
- Machine Learning Libraries (e.g., scikit-learn)
- Database (e.g., SQLite or PostgreSQL)
- Clone the repository:
git clone https://github.com/your-repo/movie-recommendation-system.git
cd movie-recommendation-system- Install the required Python packages:
pip install -r requirements.txt- Migrate the database:
python manage.py migrate- Load initial data (movies, genres, etc.):
python manage.py loaddata initial_data- Create a superuser account:
python manage.py createsuperuser- Start the development server:
python manage.py runserver- Access the application in your web browser at http://localhost:8000.
- Register or log in to your user account.
- Set your movie preferences in your user profile.
- Rate movies and add them to your viewing history.
- Explore personalized movie recommendations on your dashboard.
Explain how the machine learning models were trained, what data was used, and how the recommendations are generated. You can also include the evaluation metrics used to assess the model's performance.
If you'd like to contribute to this project, please follow these steps:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Make your changes and commit them.
- Create a pull request to the main repository.
Mention any external libraries, resources, or individuals you'd like to acknowledge.
- Jayanth ch
- Email: [email protected]
Include screenshots of the application to give users a visual idea of what to expect.
You can provide a link to a live demo of the application if available.
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