Chapter 5. Deep learning for computer vision
This chapter covers
- Understanding convolutional neural networks (convnets)
- Using data augmentation to mitigate overfitting
- Using a pretrained convnet to do feature extraction
- Fine-tuning a pretrained convnet
- Visualizing what convnets learn and how they make classification decisions
This chapter introduces convolutional neural networks, also known as convnets, a type of deep-learning model almost universally used in computer vision applications. You’ll learn to apply convnets to image-classification problems—in particular, those involving small training datasets, which are the most common use case if you aren’t a large tech company.
5.1. Introduction to convnets
We’re about to dive into the theory ...