Book Image

Hands-On Deep Learning for Images with TensorFlow

By : Will Ballard
Book Image

Hands-On Deep Learning for Images with TensorFlow

By: Will Ballard

Overview of this book

TensorFlow is Google’s popular offering for machine learning and deep learning, quickly becoming a favorite tool for performing fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations of real-world projects, teaching you how to leverage TensorFlow’s capabilities to perform efficient image processing using the power of deep learning. With the help of this book, you will get to grips with the different paradigms of performing deep learning such as deep neural nets and convolutional neural networks, followed by understanding how they can be implemented using TensorFlow. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow and Keras.
Table of Contents (7 chapters)

To get the most out of this book

You'll need:

  • Experience with command-line shell
  • Experience with Python scripting or application development

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/Hands-On-Deep-Learning-for-Images-with-TensorFlow. In 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!

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: "You just have to type docker --help to make sure that everything is installed."

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

C:\11519>docker build -t keras .

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: "We're going to select and copy the test command we'll be using later, and click on Apply."

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