A survey of Deep learning at the Edge computing
Deep learning is revolutionizing machine learning application domains such as big data analysis, computer vision, and natural language processes. Deep learning is a subset of machine learning that make use of Neural Network(NN) with many processing layers and parameters. This consumes a lot of computing power and memory during the training and testing phases. A common approach to overcoming this computational limitation of deep learning is to use cloud resources. To do this, data to be processed need to be transferred from the source to the cloud. Cloud-based big data processing presents many challenges as the amount of data continues to grow and the data processing requirements differ. Edge computing has emerged to solve these challenges. This article explores how deep learning is used in edge computing and discusses some of the common challenges that have arisen so far.