Technical approaches to business logic in model serving

In the last section, we have learned about the different types of business logic along with examples. Some business logic is exclusive to ML serving, such as data validation, feature transformation, and so on. Some business logic is common to any kind of application –  for example, user authentication, writing logs, and accessing databases. We will explain some business logic that is crucial to ML in the following sub-sections.

Data validation

Data validation is very important in serving ML models. In most of the models in our previous chapters, we have assumed the user will pass data in the right format, but that may not always be the case. For example, let’s say the model needs input in the format of [[int, int]] to make inferences, and if the user does not follow the format, we will get errors.

For example, let’s consider the following code snippet:

model = RandomForestRegressor(max_depth...