Book Image

Mastering iOS 14 Programming - Fourth Edition

By : Mario Eguiluz Alebicto, Chris Barker, Donny Wals
Book Image

Mastering iOS 14 Programming - Fourth Edition

By: Mario Eguiluz Alebicto, Chris Barker, Donny Wals

Overview of this book

Mastering iOS 14 development isn’t a straightforward task, but this book can help you do just that. With the help of Swift 5.3, you’ll not only learn how to program for iOS 14 but also be able to write efficient, readable, and maintainable Swift code that reflects industry best practices. This updated fourth edition of the iOS 14 book will help you to build apps and get to grips with real-world app development flow. You’ll find detailed background information and practical examples that will help you get hands-on with using iOS 14's new features. The book also contains examples that highlight the language changes in Swift 5.3. As you advance through the chapters, you'll see how to apply Dark Mode to your app, understand lists and tables, and use animations effectively. You’ll then create your code using generics, protocols, and extensions and focus on using Core Data, before progressing to perform network calls and update your storage and UI with the help of sample projects. Toward the end, you'll make your apps smarter using machine learning, streamline the flow of your code with the Combine framework, and amaze users by using Vision framework and ARKit 4.0 features. By the end of this iOS development book, you’ll be able to build apps that harness advanced techniques and make the best use of iOS 14’s features.
Table of Contents (22 chapters)

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...