Deep Learning

Abstract

Abstract Deep learning (DL) is a high‐dimensional data reduction technique for constructing high‐dimensional predictors in input–output models. DL is a form of machine learning that uses hierarchical layers of latent features. In this article, we review the state‐of‐the‐art of deep learning from a modelling and algorithmic perspective. We provide a list of successful areas of applications in Artificial Intelligence (AI), Image Processing, Robotics and Automation. Deep learning is predictive in its nature rather than inferential and can be viewed as a black‐box methodology for high‐dimensional function estimation.