Deep-Learning-with-PyTorch

442 CHAPTER 14 End-to-end nodule analysis, and where to go next
• TensorBoard allows us to write out many different types of diagrams that help
us determine what’s going on. But this is not a replacement for looking at data
on which our model works particularly badly.
• Successful training seems to involve an overfitting network at some stage, and
which we then regularize. We might as well take that as a recipe; and we should
probably learn more about regularization.
• Training neural networks is about trying things, seeing what goes wrong, and
improving on it. There usually isn’t a magic bullet.
• Kaggle is an excellent source of project ideas for deep learning. Many new datasets
have cash prizes for the top performers, and older contests have examples
that can be used as starting points for further experimentation.