Machine Learning from Theory to Algorithms: An Overview

TLDR

SMAC technology trends create a data‑rich environment where machine learning enables computers to imitate and adapt human‑like behavior by learning from each interaction. The paper provides an overview of machine learning as a data analytics method that learns from experience and explains why it is the future. It covers machine learning fundamentals, terminology, applications, and a technology roadmap to assess its market potential.

Abstract

The current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which is accelerating the adoption of machine learning solutions & practices. Machine Learning enables computers to imitate and adapt human-like behaviour. Using machine learning, each interaction, each action performed, becomes something the system can learn and use as experience for the next time. This work is an overview of this data analytics method which enables computers to learn and do what comes naturally to humans, i.e. learn from experience. It includes the preliminaries of machine learning, the definition, nomenclature and applications' describing it's what, how and why. The technology roadmap of machine learning is discussed to understand and verify its potential as a market & industry practice. The primary intent of this work is to give insight into why machine learning is the future.