Summary

In this chapter, we have discussed the ensemble pattern of model serving. We were introduced to the ensemble pattern and different types of approaches to using it.

We have discussed how this pattern can be of use when we need to carefully update a new model, when we need predictions from multiple models to increase the prediction accuracy, when we need an option for multiple models based on different inputs, and when we need to combine the responses from multiple models to produce a final output.

In the next chapter, we will discuss the business logic pattern to serve ML models. We will discuss how while serving an ML model, we might need different business logic, such as user authentication or querying a database.