Welcome to the workshop!
Workshop
In ProgressWelcome to Scaling and governing ML systems across the life cycle
Today's icebreaker:
Zombie model
Imagine an old ML model at your company refuses to retire. It just keeps running forever like a zombie!
What funny or disastrous things might happen if your company leaves this ‘zombie model’ in production too long?
Type your ideas in the chat.
Today's agenda:
- Review: Recap key concepts.
- **Practical exercise:**AutoDeliver life cycle challenge.
- **Closing:**Wrap-up and reflection.
Today's learning objectives:
- Evaluate scalability requirements for ML systems by analysing data variety, data quality and resource needs under varying loads.
- Design life cycle governance plans that integrate change management workflows and logging practices for production ML systems.
- Develop decommissioning and archiving protocols that ensure compliance, traceability and business continuity when retiring ML models.