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Machine Learning Projects for Mobile Applications

You're reading from   Machine Learning Projects for Mobile Applications Build Android and iOS applications using TensorFlow Lite and Core ML

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788994590
Length 246 pages
Edition 1st Edition
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Author (1):
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Karthikeyan NG Karthikeyan NG
Author Profile Icon Karthikeyan NG
Karthikeyan NG
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Toc

To get the most out of this book

If you have prior knowledge of building mobile apps, that will help greatly. If not, it is advisable to learn the basics of Java or Kotlin for Android, or Swift for iOS. 

If you have basic knowledge of Python, that will help you build your own data model, but Python skill is not mandatory. 

The applications in the book are built using a MacBook Pro. Most of the command-line operations are shown with the assumption that you have a bash shell installed on your machine. They may not work in a Windows development environment.

Download the code

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at www.packt.com.
  2. Select the SUPPORT tab.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR/7-Zip for Windows
  • Zipeg/iZip/UnRarX for Mac
  • 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Machine-Learning-Projects-for-Mobile-ApplicationsIn case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "So, we will start our iterations from 1.0 and start minimizing errors in the right direction."

A block of code is set as follows:

def estimate_house_price(sqft, location): 
price = < DO MAGIC HERE >
return price

Any command-line input or output is written as follows:

/usr/bin/ruby -e "$(curl -fsSL \
https://raw.githubusercontent.com/Homebrew/install/master/install)"

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Let's select Single View App from the initial screen, illustrated in this screenshot."

Warnings or important notes appear like this.
Tips and tricks appear like this.
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