Chapter 15. Classifying Images with Deep Convolutional Neural Networks
In the previous chapter, we looked in depth at different aspects of the TensorFlow API, became familiar with tensors, naming variables, and operators, and learned how to work with variable scopes. In this chapter, we'll now learn about Convolutional Neural Networks (CNNs), and how we can implement CNNs in TensorFlow. We'll also take an interesting journey in this chapter as we apply this type of deep neural network architecture to image classification.
So we'll start by discussing the basic building blocks of CNNs, using a bottom-up approach. Then we'll take a deeper dive into the CNN architecture and how to implement deep CNNs in TensorFlow. Along the way we'll be covering the following topics:
- Understanding convolution operations in one and two dimensions
- Learning about the building blocks of CNN architectures
- Implementing deep convolutional neural networks in TensorFlow
