July 2020
Intermediate to advanced
496 pages
9h 10m
English
Overview
This chapter covers computer vision and how this is accomplished with neural networks. You will learn to build image processing applications and classify models with convolutional neural networks. You will also study the architecture of convolutional neural networks and how to utilize techniques such as max pooling and flattening, feature mapping, and feature detection. By the end of this chapter, you will be able to not only build your own image classifiers but also evaluate them effectively for your own applications.
In the previous chapter, we explored model evaluation in detail. We covered accuracy and why it may be misleading for some datasets, especially ...