To get the most out of this book

1. We assume that you are familiar with coding in Python and the basics of TensorFlow and Keras.
2. If you haven't done already, then install Jupyter Notebooks, TensorFlow, and Keras.
3. Download the code bundle for this book that contains the Python, R, and notebook code files.

4. Practice with the code as you read along the text and try exploring by modifying the provided sample code.
5. To practice the Android chapter, you will need Android Studio and an Andrioid device.
6. To practice the iOS chapter, you will need an Apple computer with Xcode and an Apple device.
7. To practice the TensorFlow chapter, you will need Docker and Kubernetes installed. Instruction for installing Kubernetes and Docker on Ubuntu are provided in the book.

Download the example code files

You can download the example code files for this book from your account at www.packtpub.com. If you purchased this book elsewhere, you can visit www.packtpub.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.packtpub.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/Mastering-TensorFlow-1x. We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

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: "The most common practice is to use the with</kbd> block, which will be shown later in this chapter."

A block of code is set as follows:

from datasetslib.ptb import PTBSimple
ptb = PTBSimple()
ptb.load_data()
print('Train :',ptb.part['train'][0:5])
print('Test: ',ptb.part['test'][0:5])
print('Valid: ',ptb.part['valid'][0:5])
print('Vocabulary Length = ',ptb.vocab_len)

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: "Select System info from the Administration panel."

Warnings or important notes appear like this.

Tips and tricks appear like this.