Book Image

Machine Learning Projects for Mobile Applications

By : Karthikeyan NG
Book Image

Machine Learning Projects for Mobile Applications

By: Karthikeyan NG

Overview of this book

Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so. The book starts with the basics of machine learning concepts for mobile applications and how to get well equipped for further tasks. You will start by developing an app to classify age and gender using Core ML and Tensorflow Lite. You will explore neural style transfer and get familiar with how deep CNNs work. We will also take a closer look at Google’s ML Kit for the Firebase SDK for mobile applications. You will learn how to detect handwritten text on mobile. You will also learn how to create your own Snapchat filter by making use of facial attributes and OpenCV. You will learn how to train your own food classification model on your mobile; all of this will be done with the help of deep learning techniques. Lastly, you will build an image classifier on your mobile, compare its performance, and analyze the results on both mobile and cloud using TensorFlow Lite with an RCNN. By the end of this book, you will not only have mastered the concepts of machine learning but also learned how to resolve problems faced while building powerful apps on mobiles using TensorFlow Lite, Caffe2, and Core ML.
Table of Contents (16 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Building the Android application


Now create a new Android project from Android Studio. This should be called ARFilter, or whatever name you prefer:

On the next screen, select the Android OS versions that our application supports and select API 15 which is not shown on the image. That covers almost all existing Android phones. When you are ready, pressNext. On the next screen, selectAdd No Activityand click Finish. This creates an empty project:

Once the project is created, let's add one Empty Activity. We can select different activity styles based on our needs:

Name the created activity Launcher Activity by selecting the checkbox. This adds an intent filter under the particular activity in the AndroidManifest.xml file:

<intent-filter>
    <action android:name="android.intent.action.MAIN" />
    <category android:name="android.intent.category.LAUNCHER" />
</intent-filter>

Note

<intent-filter>: To advertise which implicit intents your app can receive, declare one or...