Book Image

Mastering Firebase for Android Development

By : Ashok Kumar S
Book Image

Mastering Firebase for Android Development

By: Ashok Kumar S

Overview of this book

Firebase offers a wide spectrum of tools and services to help you develop high-quality apps in a short period of time. It also allows you to build web and mobile apps quickly without managing the infrastructure.Mastering Firebase for Android Development takes you through the complete toolchain of Firebase,including the latest tools announced in Google IO 2018 such as Firebase ML-Kit, FireStore, and Firebase Predictions. The book begins by teaching you to configure your development environment with Firebase and set up a different structure for a Firebase real-time database. As you make your way through the chapters, you’ll establish the authentication feature in Android and explore email and phone authentication for managing the on-boarding of users. You’ll be taken through topics on Firebase crash reporting, Firebase functions, Firebase Cloud, Firebase Hosting, and Cloud Messaging for push notifications and explore other key areas in depth. In the concluding chapters, you will learn to use Firebase Test Lab to test your application before using Firebase Performance Monitoring to trace performance setbacks. By the end of the book, you will be well equipped with the Firebase ecosystem, which will help you find solutions to your common application development challenges.
Table of Contents (23 chapters)
Title Page
Copyright and Credits
Packt Upsell
Application Usage Measuring and Notification, Firebase Analytics, and Cloud Messaging
Bringing Everyone on the Same Page, Firebase Invites, and Firebase App Indexing
Making a Monetary Impact and Firebase AdMob and AdWords
Flexible NoSQL and Cloud Firestore
Analytics Data, Clairvoyant, Firebase Predictions

Firebase ML Kit

Ever since Google announced ML Kit, it has widely experimented with SDK, and the coding style for ML is as simple as any other Firebase toolchain service, which will ensure that experts and beginners are on the same page in understanding the tool better. ML Kit has some key capabilities, such as we can use the current beta release for the production applications for use cases such as recognizing text, detecting faces, identifying landmarks, and so on. 

ML Kit's selection APIs execute within mobile devices or in the remote cloud. The on-device APIs work quickly and draw the results even when the mobile phone is disconnected from the network. On the other hand, cloud-based APIs utilize the power of Google Cloud Platform (GCP) to produce very accurate and a higher level of results. ML Kit APIs cannot cover all the unique problems and use cases. To fill the gap, ML Kit offers a way to consume TensorFlow Lite models. Developers have to upload the models to the Firebase console...