Summary

In this chapter, we learned about the key principles of serving ML models to our users and monitoring them to achieve maximized business value. We explored the different means of serving ML models for users or consumers of the model and implemented the Explainable Monitoring framework for a hypothetical business use case and deployed a model. We carried out this hands-on implementation of an Explainable Monitoring framework to measure the performance of ML systems. Finally, we discussed the need for governing ML systems to ensure the robust performance of ML systems.

We will further explore the governance of ML systems and continual learning concepts in the next and final chapter!