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)

Deep neural network

Now, we're going to create an actual deep neural network using convolution.

In this section, we'll cover how to check to make sure we're running on a GPU, which is an important performance tip. Then, we'll load up our image data, and then we'll build a multiple block deep neural network, which is much deeper than anything we've created before. Finally, we'll compare the results of this deep neural network with our shallow convolutional neural network in the previous section.

Here, at the top, we're importing the necessary Python packages:

Importing packages

This is the same as we did for the standard convolutional neural network. The difference regarding making a deep neural network is that we're simply going to be using the same layers even more. In this next block, we're going directly to tensorflow and importing...