Deep Learning Essentials

Hierarchical feature representation

The learnt features capture both local and inter-relationships for the data as a whole, it is not only the learnt features that are distributed, the representations also come hierarchically structured. The previous figure, Comparing deep and shallow architecture. It can be seen that shallow architecture has a more flat topology, while deep architecture has many layers of hierarchical topology compares the typical structure of shallow versus deep architectures, where we can see that the shallow architecture often has a flat structure with one layer at most, whereas the deep architecture structures have multiple layers, and lower layers are composited that serve as input to the higher layer. The following ...