Inside Deep Learning

14 Advanced building blocks

This chapter covers

• Improving translation invariance with anti-aliased pooling
• Converging faster with improved residual connections
• Fighting overfitting by mixing data

The exercises in this book have thus far been designed so that you can learn about real techniques in a minimal amount of compute time. But when you work on real-world problems, they often require hundreds of epochs and models that are deeper than what you have trained so far, and they must process larger inputs than the examples in this book.

When tackling these larger data sets, it sometimes takes extra tools to get the best results. This chapter covers some of the latest and greatest techniques that researchers have developed to improve deep learning ...