The Deep Learning with PyTorch Workshop

4. Convolutional Neural Networks

Overview

This chapter explains the process of training convolutional neural networks (CNNs)—that is, the computations that occur in the different layers that can be typically found in a CNN architecture and their purpose in the training process. You will learn how to improve a computer vision model's performance by applying data augmentation and batch normalization to a model. By the end of this chapter, you will be able to use CNNs to solve image classification problems using PyTorch. This will be the starting point for implementing other solutions in the domain of computer vision.

Introduction

In the previous chapter, the most traditional neural network architecture was explained and applied to a real-life ...