Amazon SageMaker and Open-Source Tools for ML: Better Together
Learn how to augment Amazon SageMaker with open-source tools for ML, to build a robust ML Infrastructure
On-Demand Workshop
The Amazon SageMaker and Open-Source for ML is a hands-on workshop to help DevOps and Infrastructure teams, ML Engineers, MLOps professionals, and architects to learn how to mix and match fully managed AWS services and cutting-edge open-source tools for Machine Learning. The event has hands-on labs and modules on building a customizable ML infrastructure, practical cases of using Amazon SageMaker in combination with open-source components, and a live demo on ML lifecycle implementation.
Agenda:
- Overview of Modern ML Infrastructure on AWS combined with open-source components
- Real-world case study on building ML Infrastructure for Vision Screening with Amazon SageMaker and Kubeflow
- Hands-on walk-through demo of the complete ML Engineer Experience — ML Lifecycle: From Data to ML Model Deployment and Retraining
Speakers:
- Rinat Gareev, ML Solutions Architect, Provectus
- Dmitrii Evstiukhin, Senior Solutions Architect, Provectus
- Lenar Gabdrakhmanov, ML Engineer, Provectus
Who should attend:
- DevOps teams
- Infrastructure teams
- ML Engineers
- MLOps professionals
- Architects
Let’s explore industry best practices of combining Amazon SageMaker with the best open-source tools and frameworks for Machine Learning!
