Machine Learning and Its Dominant Paradigms

Abstract

Much of the human behavior depends on learning. This learning begins at a very small age in humans when a newborn starts understanding what is happening around. They get to describe what is happening which results into descriptive learning. When they analyze the cause or nature of a condition, it is called diagnostic learning. When they validate the foreseen probability of things, that is predictive learning. They tend to create definitive activities from their learning which is perspective learning. Finally, as a grown adult, when after all the learning, their actions become intuitive, that is cognitive learning. Just as humans, machines also have the capacity to learn through experience and training. Machines also have the capabilities to learn and predict, form perceptions, and take actions accordingly. All these falls under the domain of Machine Learning. Therefore, the paper will present deeper understanding of machine learning and its paradigms as well.