Book Image

Xamarin.Forms Projects - Second Edition

By : Daniel Hindrikes, Johan Karlsson
Book Image

Xamarin.Forms Projects - Second Edition

By: Daniel Hindrikes, Johan Karlsson

Overview of this book

Xamarin.Forms is a lightweight cross-platform development toolkit for building apps with a rich user interface. Improved and updated to cover the latest features of Xamarin.Forms, this second edition covers CollectionView and Shell, along with interesting concepts such as augmented reality (AR) and machine learning. Starting with an introduction to Xamarin and how it works, this book shares tips for choosing the type of development environment you should strive for when planning cross-platform mobile apps. You’ll build your first Xamarin.Forms app and learn how to use Shell to implement the app architecture. The book gradually increases the level of complexity of the projects, guiding you through creating apps ranging from a location tracker and weather map to an AR game and face recognition. As you advance, the book will take you through modern mobile development frameworks such as SQLite, .NET Core Mono, ARKit, and ARCore. You’ll be able to customize your apps for both Android and iOS platforms to achieve native-like performance and speed. The book is filled with engaging examples, so you can grasp essential concepts by writing code instead of reading through endless theory. By the end of this book, you’ll be ready to develop your own native apps with Xamarin.Forms and its associated technologies, such as .NET Core, Visual Studio 2019, and C#.
Table of Contents (13 chapters)

Project overview

If you have seen the TV series Silicon Valley, you have probably heard of the Not Hotdog application. In this chapter, we will learn how to build that app. The first part of this chapter will involve collecting the data that we will use for creating a machine learning model that can detect whether or not a photo contains a hot dog.

In the second part of the chapter, we will build an app for iOS and an app for Android, whereby the user can pick a photo in the photo library in order to analyze it to see whether it contains a hot dog. The estimated time for completing this project is 120 minutes.