As Francois Chollet in his book “Deep Learning with Python” has defined “Deep learning is a SPECIFIC SUBFIELD of machine learning: a new take on learning representations from data that puts an emphasis on learning successive layers of increasingly meaningful representations.” The deep in deep learning does not necessarily refer to any kind of “deeper understanding achieved by the approach; rather, it stands for the idea of successive layers of representations. How many layers contribute to a model of the data is called the depth of the model. 

Other appropriate names for the field could have been LAYERED representations learning and hierarchical representations learning. Modern deep learning often involves tens or even HUNDREDS of successive layers of representations— and they’ve all learned automatically from exposure to training data. Meanwhile, other approaches to machine learning tend to focus on learning only one or two layers of representations of the data; hence, they’re sometimes called shallow learning.” (PLEASE refer to the Book – “Deep Learning with Python” by Francois Chollet)