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Practical Android AI

First Edition · Android 13 · Kotlin 2.0 · Android Studio Otter

Before You Begin

Section 0: 5 chapters
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Section I: Foundations of AI on Android

Section 1: 3 chapters
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Section II: Building Core Intelligence

Section 2: 3 chapters
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Section III: Advanced Integration, Distribution, and Responsible AI

Section 3: 4 chapters
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i. What You Need
Written by Zahidur Rahman Faisal

To follow the examples and exercises in this book, you will need a combination of software, hardware, and Google accounts. The items below cover the general prerequisites referenced throughout the chapters.

Development environment

  • Android Studio (Otter): It’s recommended to use the latest stable version of Android Studio and the SDK components (Android SDK Platform, emulator images). The minimum version of Android Studio supported by this book is Otter.

  • Android 6+: The minimumSdkVersion for the projects is API 23, so you need a device or an emulator running API 23 or higher.

  • Kotlin 2.0 (or higher): You need Kotlin 2.0 or higher to run the sample projects. Use the Kotlin plugin bundled with the latest Android Studio releases, or the version indicated by the sample projects.

  • Command-line Tools:

    • Git for source control.
    • adb (comes with Android SDK Platform Tools) for device interaction.
    • bundletool to convert an App Bundle with custom models into testable APKs.

Hardware

  • A modern development laptop/desktop (macOS, Linux, or Windows) with at least:
    • 8 GB of RAM.
    • At least 20 GB of free disk space (for models, libraries, or emulators).
  • Android device (or Emulator):
    • A physical Android device is highly recommended when working with camera-based Vision APIs and building interactive apps.
    • Optionally, an emulator (x86 image) with at least 4 GB available space, with camera and microphone access.

Accounts & Cloud Services

  • Firebase Project with Billing Profile: Basic generative AI features are free, but some advanced features like image generation may require setting up a billing profile.
  • Generative AI API keys: For chapters that call generative models, you will need Google/Firebase API keys. Follow the instructions provided and set usage limits to control costs.
  • App Signing Key (Keystore): For replicating deployment and delivery with AI bundles, you will need to create a keystore file (.jks or .keystore) and generate a private signing key using keytool.
ii. Book Source Code & Forums
Have a technical question? Want to report a bug? You can ask questions and report bugs to the book authors in our official book forum here.
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