What is machine learning?

Abstract

Over the last six decades, several pioneers of the industry have worked to steer us in the right direction. There are a number of different algorithms that one can employ in machine learning (ML). The required output is what decides which to use. ML algorithms characteristically fall into one of two learning types: supervised or unsupervised learning. ML is widely used in software to enable an improved experience with the user. Using ML, robots can acquire skills or learn to adapt to the environment in which they are working. Robots can acquire skills such as object placement, grasping objects, and locomotion skills through either automated learning or learning via human intervention. The race is on for ML to be used in healthcare analytics. A number of start-ups are looking at the advantages of using ML with big data to provide healthcare professionals with better-informed data to enable them to make better decisions.