Deep learning is a subfield of machine learning, i.e. in deep learning we are dealing with algorithms which learn from examples, similar to machine learning. The main difference between deep learning and machine learning is that deep learning models have a notion of multiple layers or multiple levels of hierarchy, which opens up the possibility of being able to learn models for more complicated tasks.

The following are some different ways of thinking about the multiple layers of hierarchy in a deep learning model:

use a cascade of many layers of transformation. Each successive layer uses the output from the previous layer as input.

are based on the (unsupervised) learning of multiple levels of features or representations of the data. Higher level features are derived from lower level features to form a hierarchical representation.

learn multiple levels of representations that correspond to different levels of abstraction; the levels form a hierarchy of concepts.