{"id":20863905,"url":"https://github.com/eziodevio/mlops","last_synced_at":"2025-12-28T04:15:34.367Z","repository":{"id":236103215,"uuid":"791814553","full_name":"EzioDEVio/MLOps","owner":"EzioDEVio","description":"MLOps deploying house estimate model","archived":false,"fork":false,"pushed_at":"2024-11-06T14:07:21.000Z","size":36,"stargazers_count":6,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-01-19T08:16:27.274Z","etag":null,"topics":["flask-application","mlops","mlops-project","mlops-workflow"],"latest_commit_sha":null,"homepage":"","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/EzioDEVio.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-04-25T12:27:45.000Z","updated_at":"2024-12-14T20:16:32.000Z","dependencies_parsed_at":"2024-11-06T15:19:35.144Z","dependency_job_id":"0c699095-3561-4aac-ab1a-2a2c1874a7a2","html_url":"https://github.com/EzioDEVio/MLOps","commit_stats":null,"previous_names":["eziodevio/mlops"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EzioDEVio%2FMLOps","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EzioDEVio%2FMLOps/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EzioDEVio%2FMLOps/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EzioDEVio%2FMLOps/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/EzioDEVio","download_url":"https://codeload.github.com/EzioDEVio/MLOps/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243236668,"owners_count":20258884,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["flask-application","mlops","mlops-project","mlops-workflow"],"created_at":"2024-11-18T05:34:19.919Z","updated_at":"2025-12-28T04:15:34.362Z","avatar_url":"https://github.com/EzioDEVio.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![MLOps with Python application](https://github.com/EzioDEVio/MLOps/actions/workflows/main.yml/badge.svg)](https://github.com/EzioDEVio/MLOps/actions/workflows/main.yml)   [![Build and Push Docker image to Github Container Registry](https://github.com/EzioDEVio/MLOps/actions/workflows/GHCR.yml/badge.svg)](https://github.com/EzioDEVio/MLOps/actions/workflows/GHCR.yml)\r\n![Stars](https://img.shields.io/github/stars/EzioDEVio/MLOps?style=social)\r\n![MIT License](https://img.shields.io/github/license/EzioDEVio/MLOps)\r\n![Repo Size](https://img.shields.io/github/repo-size/EzioDEVio/MLOps)\r\n![Last Commit](https://img.shields.io/github/last-commit/EzioDEVio/MLOps?color=blue)\r\n\r\n# MLOps Application for Real Estate Price Prediction\r\n\r\nThis project demonstrates the application of Machine Learning Operations (MLOps) principles to a real estate price prediction model. It includes setting up a Flask application to serve predictions from a trained model and deploying this application using Docker and integrating it into a CI/CD workflow.\r\n\r\n## Project Structure\r\n\r\n- `app/`: Contains the Flask application files.\r\n  - `server.py`: The Flask server file with API endpoints.\r\n- `models/`: Contains the trained model file.\r\n  - `california_housing_model.joblib`: Pre-trained scikit-learn model.\r\n- `templates/`: HTML files for the application frontend.\r\n- `static/`: CSS and JS files for the frontend.\r\n- `Dockerfile`: Contains all the commands to assemble the app Docker image.\r\n- `requirements.txt`: List of packages required for the application.\r\n\r\n## Setup and Installation\r\n\r\n### Prerequisites\r\n\r\n- Python 3.8+\r\n- pip\r\n- virtualenv (optional)\r\n\r\n### Local Setup\r\n\r\n1. **Clone the Repository:**\r\n\r\n   ```bash\r\n   git clone https://github.com/EzioDEVio/MLOps.git\r\n   cd MLOps\r\n   ```\r\n\r\n2. **Create and Activate a Virtual Environment (optional):**\r\n\r\n   Windows:\r\n   ```bash\r\n   python -m venv venv\r\n   venv\\Scripts\\activate\r\n   ```\r\n\r\n   macOS/Linux:\r\n   ```bash\r\n   python3 -m venv venv\r\n   source venv/bin/activate\r\n   ```\r\n\r\n3. **Install Dependencies:**\r\n\r\n   ```bash\r\n   pip install -r requirements.txt\r\n   ```\r\n\r\n4. **Run the Application:**\r\n\r\n   ```bash\r\n   python app/server.py\r\n   ```\r\n\r\n   Visit `http://127.0.0.1:5000` in your web browser to view the app.\r\n\r\n## Docker Deployment\r\n\r\n1. **Build the Docker Image:**\r\n\r\n   ```bash\r\n   docker build -t mlops-app .\r\n   ```\r\n\r\n2. **Run the Docker Container:**\r\n\r\n   ```bash\r\n   docker run -p 5000:5000 mlops-app\r\n   ```\r\n\r\n   The application should now be accessible at `http://localhost:5000`.\r\n\r\n## CI/CD Integration\r\n\r\nThis project uses GitHub Actions for Continuous Integration and Continuous Deployment (CI/CD).\r\n\r\n### Workflow\r\n\r\n1. **Continuous Integration:**\r\n\r\n   - Build the Docker image.\r\n   - Run tests (add your tests in the workflow).\r\n\r\n2. **Continuous Deployment:**\r\n\r\n   - Push the Docker image to a registry (e.g., Docker Hub).\r\n   - Deploy the image to a cloud service (e.g., AWS, Azure).\r\n\r\n### Setup GitHub Actions\r\n\r\n1. **Create a `.github/workflows` directory in your repository.**\r\n\r\n2. **Add a workflow file (e.g., `ci-cd.yml`):**\r\n\r\n   ```yaml\r\n   name: CI/CD Pipeline\r\n\r\n   on:\r\n     push:\r\n       branches: [ main ]\r\n     pull_request:\r\n       branches: [ main ]\r\n\r\n   jobs:\r\n     build:\r\n       runs-on: ubuntu-latest\r\n       steps:\r\n       - uses: actions/checkout@v2\r\n       - name: Set up Python\r\n         uses: actions/setup-python@v2\r\n         with:\r\n           python-version: '3.8'\r\n       - name: Install dependencies\r\n         run: |\r\n           python -m pip install --upgrade pip\r\n           pip install -r requirements.txt\r\n       - name: Build Docker image\r\n         run: docker build -t mlops-app .\r\n       # Add additional steps for testing and deployment\r\n   ```\r\n\r\n## Contributing\r\n\r\nContributions to this project are welcome! Please fork the repository and submit a pull request with your proposed changes.\r\n\r\n## License\r\n\r\nMIT.\r\n\r\n\r\n.\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feziodevio%2Fmlops","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Feziodevio%2Fmlops","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feziodevio%2Fmlops/lists"}