DEEP LEARNING: PREVIOUS AND PRESENT APPLICATIONS

Abstract

Deep learning is an emerging area of machine learning (ML). It comprises multiple hidden layers of artificial neural networks. The deep learning methodology applies nonlinear transformations and model abstractions of high level in large databases. The recent advancements in deep learning architectures within numerous fields have already provided significant contributions in artificial intelligence. The following review chronologically presents how and in what major applications deep learning algorithms have been utilized. Furthermore, the superior and beneficial of the deep learning methodology and its hierarchy in layers and nonlinear operations are presented and compared with the more conventional algorithms in the common applications. All in all, the purpose of this review is to give a general concept of deep learning and how its advantages have improved during the last years.