{"id":25907954,"url":"https://github.com/vamshikrishna779/cine-match","last_synced_at":"2026-04-09T21:54:34.052Z","repository":{"id":277670597,"uuid":"933157762","full_name":"Vamshikrishna779/Cine-Match","owner":"Vamshikrishna779","description":"AI-powered movie recommendations using collaborative and content-based filtering. Built with Python and Streamlit. 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It employs collaborative and content-based filtering techniques to enhance the user experience on movie platforms. Built using Python and Streamlit, this project processes movie metadata and user behavior to generate relevant suggestions.  \n\n## Features  \n- Search and browse movies from the dataset  \n- Generate personalized movie recommendations  \n- Machine learning-based filtering techniques  \n- Fast performance with precomputed similarity matrices  \n- Interactive web interface using Streamlit  \n\n## Technologies Used  \n- Python  \n- Streamlit  \n- Scikit-learn  \n- Pandas  \n- NumPy  \n- Pickle (for model persistence)  \n\n## Project Structure  \n```\n├── .ipynb_checkpoints         # Jupyter notebook checkpoints\n├── .venv                      # Virtual environment (optional)\n├── screenshots                # Folder for UI screenshots\n├── template                   # Template files\n├── app.py                        # Main application\n├── movie_dict.pkl         # Serialized movie dataset\n├── similarity.pkl         # Serialized similarity matrix\n├── model.pkl              # Serialized recommendation model\n├── requirements.txt       # Dependencies\n├── BDTProject                 # Additional project files\n├── README.md                  # Project documentation\n```\n\n## Installation and Setup  \n1. Clone the repository:  \n   ```sh\n   git clone https://github.com/your-username/movie-recommender.git\n   cd movie-recommender\n   ```\n2. Create a virtual environment (optional but recommended):  \n   ```sh\n   python -m venv venv\n   source venv/bin/activate  # On Windows use `venv\\Scripts\\activate`\n   ```\n3. Install dependencies:  \n   ```sh\n   pip install -r requirements.txt\n   ```\n4. Run the Streamlit app:  \n   ```sh\n   streamlit run app.py\n   ```\n5. Open the browser and go to **http://localhost:8501/** to access the app.  \n\n## User Interface  \n### Home Page  \nDisplays an introduction and an overview of the app.  \n\n### Movies Page  \n- Allows users to browse and search for movies.  \n- Retrieves metadata and details for selected movies.  \n\n### Recommendations Page  \n- Users can select a movie they like.  \n- The system generates and displays recommendations based on machine learning models.  \n\n## Results and Evaluation  \n- High recommendation accuracy based on user interactions and preferences.  \n- Optimized performance using precomputed similarity matrices.  \n- Positive user feedback on relevant and engaging recommendations.  \n\n## Contact  \nFor any queries, feedback, or collaboration opportunities, reach out to:  \n- GitHub: [Vamshikrishna779](https://github.com/Vamshikrishna779)  \n\n\n## License  \nThis project is licensed under the MIT License.  \n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvamshikrishna779%2Fcine-match","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvamshikrishna779%2Fcine-match","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvamshikrishna779%2Fcine-match/lists"}