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)

A Convolutional Neural Network

In the previous chapter, we learned all about dense neural networks.

In this chapter, we're going to move on to a more recent technique: the convolutional neural network. This is an approach that you can use to process a wide array of images, and you'll find that, as we show you how it works, it's actually much more accurate and effective than the classical neural network.

In this section, we're going to learn all about convolutions and how to apply them to images, and then we're going to learn about another operation known as pooling. Armed with these two new techniques, we're going to build an actual convolutional neural network and train it in our MNIST digits, which will reveal that it's much more accurate. Finally, we're going to build an actual deep network. The idea behind deep learning is that you take...