In this webinar, we’ll learn how to implement the 1st level of MLOps maturity and perform continuous training of the model by automating the ML pipeline. We'll start with the ML pipeline and see how we can detect performance degradation and data drift in order to trigger the pipeline and create a new model based on fresh data.
What will you learn:
- See an example of an ML pipeline implementation using Flyte
- Deploy model to an endpoint
- Define monitoring policies (include some best practices)
- Trigger ML pipeline to create a new model based on fresh data
