ABSTRACT
Generating knowledge from data increasingly requires the use of machine learning for various reasons—cognitive, organizational, technical, and operational. While there are a plethora of books, videos, websites, and other resources on machine learning, most content is either too generic or, on the other end of the spectrum, requires an advanced understanding of linear algebra, probability, statistics, and/or computer science.AI and machine learning are not new topics. “Machine Learning (ML) is a paradigm that enables systems to automatically improve their performance at a task by observing relevant data.” A learning algorithm is an algorithm that is able to use all types of data and metadata to learn continuously and progressively. A learning algorithm uses data and experience to self-learn and to perform better over time. Learners are the foundation of any ML system, and they help people achieve generalization via induction or abduction.
