47.6K-Star GitHub Repo Teaches Full ML Lifecycle From Training to Production Deployment
Summary
A massively popular 47.6K-star GitHub repository called Made With ML is teaching developers the complete machine learning lifecycle—from training and tuning to production deployment—using MLOps best practices, MLflow experiment tracking, Ray-powered cloud scaling, and fully automated CI/CD pipelines via GitHub Actions.
Key Points
- Made With ML is a GitHub repository with 47.6k stars that teaches developers how to design, develop, deploy, and iterate on production-grade machine learning applications using best practices and MLOps principles.
- The course covers the full ML lifecycle including training, tuning, experiment tracking with MLflow, evaluation, serving, and testing, with support for both local environments and scalable cloud deployments via Anyscale and Ray.
- A complete CI/CD pipeline using GitHub Actions is provided, enabling automated model training and deployment workflows that support continual learning through integration with data pipelines, monitoring, and scheduled runs.