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)

Summary

In this chapter, you have seen how you can make use of the machine learning capabilities that iOS provides. You saw that adding a machine learning model to your app is extremely simple since you only have to drag it to Xcode and add it to your target app. You also learned how you can obtain models, and where to look to convert existing models to Core ML models. Creating a machine learning model is not simple, so it's great that Apple has made it so simple to implement machine learning by embedding trained models in your apps.

In addition to Core ML, you also learned about the Vision and Natural Language frameworks. Vision combines the power of Core ML and smart image analysis to create a compelling framework that can perform a massive amount of work on images. Convenient requests, such as facial landmark detection, text analysis, and more are available out of the box without adding any machine learning models to your app. If you do find that you need more power in the...