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)

Summary

In this chapter, we learned about the MNIST digits, and how to acquire them; how tensors are really just multidimensional arrays; how we can encode image data as a tensor; how we can encode categorical or classification data as a tensor; and then we had a quick review and a cookbook approach to think about dimensions and tensors to get data prepared for machine learning.

Now that we've learned how to set up our input and output data for machine learning, we're going to move on to the next chapter, where we will create a Classical Neural Network (CNN).