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 modeling 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 then inferential and can be viewed as a black-box methodology for high-dimensional function estimation.

翻译：深层学习(DL)是一种高维数据减少技术,用于在输入输出模型中构建高维预测器。 DL是一种机器学习形式,使用潜伏特征的层次层。在本条中,我们从建模和算法的角度审查深层学习的最新技术。我们提供了人工智能(AI)、图像处理、机器人学和自动化方面的成功应用领域清单。深层学习在性质上是预测性的,而不是推断性的,可以被视为高维函数估计的黑盒方法。