{"id":28735240,"url":"https://github.com/vortico/mlops-course","last_synced_at":"2026-03-07T00:32:22.041Z","repository":{"id":298501568,"uuid":"914344115","full_name":"vortico/mlops-course","owner":"vortico","description":"Course materials for MLOps, focusing on deploying and managing ML systems in production.","archived":false,"fork":false,"pushed_at":"2025-03-28T10:14:30.000Z","size":6424,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-08-25T14:56:39.199Z","etag":null,"topics":["flama","machine-learning","mlops","mlops-workflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/vortico.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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,"zenodo":null}},"created_at":"2025-01-09T12:14:26.000Z","updated_at":"2025-06-10T09:49:24.000Z","dependencies_parsed_at":"2025-06-11T12:48:32.825Z","dependency_job_id":"56c79b7b-d123-41f3-9adc-b018346cb88e","html_url":"https://github.com/vortico/mlops-course","commit_stats":null,"previous_names":["vortico/mlops-course"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/vortico/mlops-course","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vortico%2Fmlops-course","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vortico%2Fmlops-course/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vortico%2Fmlops-course/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vortico%2Fmlops-course/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vortico","download_url":"https://codeload.github.com/vortico/mlops-course/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vortico%2Fmlops-course/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30204154,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-06T19:07:06.838Z","status":"ssl_error","status_checked_at":"2026-03-06T18:57:34.882Z","response_time":250,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["flama","machine-learning","mlops","mlops-workflow"],"created_at":"2025-06-16T00:14:25.689Z","updated_at":"2026-03-07T00:32:22.022Z","avatar_url":"https://github.com/vortico.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MLOps and ML Engineering Course\n\n## Overview\n\nWelcome to the MLOps and ML Engineering course! This repository contains practical materials and examples for learning modern Machine Learning Operations (MLOps) and engineering best practices. The course is designed to bridge the gap between data science and production-ready ML systems.\n\n## 🚀 Quick Start\n\n1. Clone this repository\n\n2. Install dependencies:\n\n```bash\nmake install-dev\n```\n\n3. Start the model server\n\n```bash\nmake model-serve\n```\n\n## 📚 Repository Documentation\n\nYou can find the documentation in the [`docs/`](./docs/) directory:\n\n- `cicd/` - CI/CD pipeline implementation and practices\n- `dev-env/` - Python environment management with pyenv and poetry\n- `make/` - Automation and Makefile usage guide\n- `package/` - MLOps package structure and implementation\n- `airflow/` - Airflow DAGs and configuration\n- `mlflow/` - MLflow configuration and best practices\n- `package/` - MLOps package structure and implementation\n\n## 🛠 Development Tools\n\nThis project uses modern Python development tools and practices:\n\n### Key Make Commands\n\n```bash\nairflow-start                  Start serving airflow\nairflow-stop                   Start serving airflow\nblack                          Runs black\ninstall-dev                    Installs the project (with dev dependencies)\ninstall                        Installs the project (only main dependencies)\nisort                          Runs isort\nlint-fix                       Runs a linting pipeline with auto fixing: black, isort, ruff, and mypy\nlint                           Runs linting tools\nmodel-serve                    Serves the model in local environment\nmodel-start                    Start serving the model container\nmodel-stop                     Stop serving the model container\npyright                        Runs pyright\nruff                           Runs ruff\ntest                           Runs tests\n```\n\n### Development Environment\n\n- **Python Version**: 3.13\n- **Package Management**: Poetry\n- **Code Quality**: black, isort, ruff, pyright\n- **Testing**: pytest\n- **Model Serving**: Flama\n- **Model Deployment**: Docker\n- **Model Registry**: mlflow\n- **Orchestration**: airflow\n\n## 🎯 Learning Objectives\n\nThis course covers:\n\n- Setting up professional ML development environments\n- Implementing CI/CD for ML projects\n- Building production-ready ML pipelines\n- Best practices for model deployment\n- Code quality and testing in ML projects\n\n## 📖 Documentation\n\nDetailed documentation is available in the `docs/` directory:\n\n- [CI/CD Implementation](docs/cicd/README.md)\n- [Development Environment Setup](docs/dev-env/README.md)\n- [Make and Automation](docs/make/README.md)\n- [Package Structure](docs/package/README.md)\n\n## 🤝 Contributing\n\n1. Ensure you have all development dependencies installed\n2. Make your changes\n3. Run the full test suite:\n\n```bash\nmake lint \u0026\u0026 make test\n```\n\n4. Submit your pull request\n\n## 📝 License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvortico%2Fmlops-course","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvortico%2Fmlops-course","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvortico%2Fmlops-course/lists"}