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/

https://github.com/rfashwall/ml-con-workshop/wiki