8 Using convolutions to generalize

This chapter covers

  • Understanding convolution
  • Building a convolutional neural network
  • Creating custom nn.Module subclasses
  • The difference between the module and functional APIs
  • Design choices for neural networks

In the previous chapter, we built a simple neural network that could fit (or overfit) the data, thanks to the many parameters available for optimization in the linear layers. We had issues with our model, however, in that it was better at memorizing the training set than it was at generalizing properties of birds and airplanes. Based on our model architecture, we’ve got a guess as to why that’s the case. Due to the fully connected setup needed to detect the various possible translations of the bird ...

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