Machine Learning Requires Big Data - DZone Big Data

During the Deep Learning Summit at AWS re:Invent 2017, Terrence Sejnowski (a pioneer of deep learning) succinctly said, "Whoever has more data wins." He was echoing a premise that has been repeated many times in many ways by many people: machine learning requires big data to work. That's why here at Qubole we believe that enabling data scientists starts with giving them a platform to quickly select, clean, and aggregate datasets on a massive scale. The recent surge in impactful applications of deep learning algorithms has misled many people to believe that there has been a corresponding upswell in innovation in this field. Although there are indeed new bleeding-edge algorithms being released (most recently, Geoffrey Hinton's milestone capsule networks), most of the deep learning algorithms used in innovative technologies are actually decades old.