Summary
In this chapter, we learned about the key principles for monitoring an ML system. We explored some common monitoring methods and the Explainable Monitoring Framework (including the monitor, analyze, and govern stages). We then explored the concepts of Explainable Monitoring thoroughly.
In the next chapter, we will delve into a hands-on implementation of the Explainable Monitoring Framework. Using this, we will build a monitoring pipeline in order to continuously monitor the ML system in production for the business use case (predicting weather at the port of Turku).
The next chapter is quite hands-on, so buckle up and get ready!
