David Aronchick, Head of OSS ML Strategy at Microsoft, Marvin Buss, Azure Customer Engineer at Microsoft, and Zander Matheson, Senior Data Scientist at Github discuss using Git to enable continuous delivery of machine learning to production, enable controlled collaboration across ML teams, and solve rigorous MLOps needs.
In this session you will learn how to:
• Enable continuous delivery of machine learning to production using Git-based ML pipelines (Github Actions) with hosted training and model serving environments
• Leverage Git to solve rigorous MLOps needs: automating workflows, reviewing models, storing versioned models as artifacts, and running CI/CD for ML
• Enable controlled collaboration across ML teams using Git review processes
• Implement an MLOps solution based on available open-source tools and hosted ML platforms (live demo)
This blog has been republished by AIIA. To view the original article, please click HERE.