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 ...

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