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Mobile Artificial Intelligence Projects

You're reading from  Mobile Artificial Intelligence Projects

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789344073
Pages 312 pages
Edition 1st Edition
Languages
Authors (3):
Karthikeyan NG Karthikeyan NG
Profile icon Karthikeyan NG
Arun Padmanabhan Arun Padmanabhan
Profile icon Arun Padmanabhan
Matt Cole Matt Cole
Profile icon Matt Cole
View More author details

Table of Contents (12) Chapters

Preface 1. Artificial Intelligence Concepts and Fundamentals 2. Creating a Real-Estate Price Prediction Mobile App 3. Implementing Deep Net Architectures to Recognize Handwritten Digits 4. Building a Machine Vision Mobile App to Classify Flower Species 5. Building an ML Model to Predict Car Damage Using TensorFlow 6. PyTorch Experiments on NLP and RNN 7. TensorFlow on Mobile with Speech-to-Text with the WaveNet Model 8. Implementing GANs to Recognize Handwritten Digits 9. Sentiment Analysis over Text Using LinearSVC 10. What is Next? 11. Other Books You May Enjoy

Creating an Android app to predict house prices

In this section, we are going to consume the model through the RESTful API via an Android app. The purpose of this section is to demonstrate how a model can be consumed and used by an Android app. Here, we have assumed that you are familiar with the basics of Java programming. The same approach can be used for any similar use case, even on web apps. The following steps are covered in this section:

  • Downloading and installing Android Studio
  • Creating a new Android project with a single screen
  • Designing the layout of the screen
  • Adding a functionality to accept input
  • Adding a functionality to consume the RESTful API that serves the model
  • Additional notes

Downloading and installing Android Studio

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