Technical Workshop
Federated Learning and the Scaleout Edge Platform: A Practical Session
A technical walkthrough for data scientists and ML engineers focusing on the practical requirements of establishing a federated learning architecture within an enterprise environment.
This workshop covers the workflow for setting up a machine learning federation. We will demonstrate the Scaleout Edge platform's capabilities and how the architecture integrates into standard MLOps pipelines without requiring data movement.
Agenda
- 15 min Framework overview and architectural patterns for ML federation.
- 45 min Practical demonstration: Establishing a federation and training a model across distributed nodes.
- 15 min Questions and answers.
Technical Participation (Optional)
Attendees can participate as a federated client during the live demonstration. This requires setting up a local client to connect to the workshop federation.
Prerequisites
- Terminal proficiency (Bash, Zsh, or PowerShell)
- Python 3.9 or higher
- pip installed and configured
If you intend to participate as a client, please indicate this in the registration message so we can provide the necessary configuration files ahead of time.
Availability
Attendance is capped at 20 participants to allow for technical troubleshooting. The session is open to Scaleout partners and customers.
For those requiring a private session tailored to specific infrastructure, please include a note in your registration.