ML is not alone
Chapter 2 introduced several elements of an ML system – storage, data collection, monitoring, and infrastructure, just to name a few of them. We need all of them to deploy a model for the users, but not all of them are important for the users directly. We need to remember that the users are interested in the results, but we need to pay attention to all details related to the development of such systems. These activities are often called AI engineering.
The UI is important as it provides the ability to access our models. Depending on the use of our software, the interface can be different. So far, we’ve focused on the models themselves and on the data that is used to train the models. We have not focused on the usability of models and how to integrate them into the tools.
By extension, as for the UI, we also need to talk about storing data in ML. We can use comma-separated values (CSV) files, but they quickly become difficult to handle. They are either...
