A hands-on workshop covering the complete journey from ML model development to production deployment using industry-standard tools.
This 6-hour intensive workshop teaches you to deploy and maintain machine learning models in production. Through progressive hands-on modules, you'll work with Kubernetes, MLflow, BentoML, and Kubeflow to build production-ready ML systems.
What You'll Learn:
- Model versioning with Hugging Face Hub and MLflow
- Containerization with Docker and BentoML
- Kubernetes deployment and scaling
- Production monitoring and observability
- CI/CD pipelines for ML models
Setup Options:
- Local (macOS): Python 3.11+, Docker Desktop, kubectl, kind
- GitHub Codespaces: Pre-configured cloud environment
https://www.linkedin.com/in/rabieh-fashwall/
