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)

Activation and nonlinearity

We're going to be talking about why nonlinearity matters, and then we'll look at some visualizations of the two most commonly used nonlinear functions: sigmoid and relu.

So, nonlinearity may sound like a complicated mathematical concept, but all you basically need to know is that it doesn't go in a straight line. This allows neural networks to learn more complex shapes, and this learning of complex shapes inside of the structure of the network is what lets neural networks and deep learning actually learn.

So, let's take a look at the sigmoid function:

Sigmoid function

It's kind of an S-curve that ranges from zero to one. It's actually built out of e to an exponent and a ratio. Now, the good news is that you'll never actually have to code the math that you see here, because when we want to use sigmoid in Keras, we...