A subcategory of machine learning, deep learning permits hierarchical learning of a large quantity of information.
In other words, the machine processes the data in order of complexity to understand a reality and grasp it through its own means with the aid of a neural network. The name deep learning alludes to the fact that the system functions in layers.
As Yann Ollivier, Director of Research at the French National Center for Scientific Research (CNRS) and a specialist in artificial intelligence, explains, the results from the first layer of neurons serve as a point of departure for calculating subsequent results.
In order to distinguish a picture of a cat from a picture of a dog, a machine must compare increasingly complex characteristics based on the lessons learned, for example, the fact that the ears of the two animals are shaped differently.
