Machine learning (ML) and artificial intelligence (AI) algorithms are increasingly powering our modern society and leaving their mark on everything from finance, healthcare, to transportation. If the late half of the 20th century was about the general progress in computing and connectivity (internet infrastructure), the 21st century is shaping up to be dominated by intelligent computing and a race toward smarter machines.
Most of the discussion and awareness about these novel computing paradigms, however, circle around the so-called ‘supervised learning’, in which deep learning (DL) occupies a central position. The recent advancement and astounding success of deep neural networks (DNN) – from disease classification to image segmentation to speech recognition – has led to much excitement and application of DNNs in all facets of high-tech systems.