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  • Book Overview & Buying Flutter for Beginners
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Flutter for Beginners

Flutter for Beginners - Fourth Edition

By : Thomas Bailey, Alessandro Biessek
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Flutter for Beginners

Flutter for Beginners

By: Thomas Bailey, Alessandro Biessek

Overview of this book

The Fourth edition of Flutter for Beginners is fully updated for the latest Flutter and Dart releases, ready to guide you from taking your first steps in Flutter to publishing your first cross-platform app. Designed for new developers and those transitioning from other technologies, this practical guide shows you how to build, test, and release high-quality mobile apps for iOS, Android, and the web. With a project-based approach, this book will help you master the fundamentals of Dart and Flutter’s widget-driven architecture while building a complete app from scratch. Each chapter builds on the last with step-by-step explanations that will teach you how to design beautiful interfaces, manage state, handle navigation and user input, and add animations that bring your UI to life. You’ll explore popular third-party plugins such as Firebase and Google Maps, learn to debug and test your code effectively, and prepare your app for release on multiple platforms. By the end of this book, you’ll have the hands-on experience and confidence to design, build, and publish your own Flutter apps using the latest best practices.
Table of Contents (23 chapters)
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1
Part 1: Learning the Core Concepts
6
Part 2: Building a Basic Flutter App
11
Part 3: Turning a Simple App into an Awesome App
16
Part 4: Testing and Releasing Your App
19
Chapter 16: Free Benefits with Your Book
20
Other Books You May Enjoy
21
Index

Machine learning

The term artificial intelligence (AI) is an overloaded term that can apply to a vast array of technologies. For software development, the relevant part of AI that seems to be having great success is machine learning. This technology is behind features such as allowing your app to interpret the contents of an image or predict the likely products you may purchase based on your previous purchase history.

Machine learning tooling effectively learns from large quantities of marked-up training data, such as images with descriptions or product baskets with items in them. It can then extrapolate based on an individual example (e.g., a picture or a single purchase history) against this training data to predict the likelihood that the picture contains a cat or that the purchaser will need to buy a can of drink.

You will have seen examples of this in Spotify predicting the next song, Amazon suggesting that people who bought this item also bought these other items, or photography...

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Tech Concepts
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Programming languages
73
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Flutter for Beginners
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