Updating models remotely with Model Deployment

One of the new features of iOS 14 for machine learning is the ability to keep collections of your models in the cloud, giving you the power to update them at any time without the need to update the app itself.

We are going to use a project, available in the code bundle of this book, in order to demonstrate this new feature. The project's name is TextAnalyzerCloud. It is the same project that we used before, but this time, the model will be on the cloud (with a local copy as a fallback).

There are two steps involved in order to use Model Deployment in our apps:

1. Use the Core ML API to retrieve collections of models.
2. Prepare and deploy the model.

Let's implement these steps in the next subsections.

Using the Core ML API to retrieve collections of models

Let's start by learning how to retrieve models that are stored in the cloud into your app. Open the TextAnalyzerCloud project in the code bundle...