Augmented-Data

• given the findings of the previous chapter (universality), why would we concern ourselves with learning deep neural nets?
  • especially given that we are guaranteed to be able to approximate any function with just a single layer of hidden neurons?

well, just because something is possible, it doesn’t mean it’s a good idea!

considering that we are using computers, it’s usually a good idea to break the problem down into smaller sub-problems, solve those, and then come back to solve the main problem.

notes#

• topics: convolutions, pooling, GPUs (to do more training), algorithmic expansion of data (reduce overfitting), dropout (also reduce overfitting), ensembles of networks

  Read more >