What is Machine Learning?

To get a handle on the buzz words used when chatting about Machine Learning a subset of Artificial Intelligence which focuses on the ability of machines to receive a set of data and learn for themselves from data they are processing, here is a simple non-technical explanation for the common Machine Learning concepts with examples of applications.

Tip: Machine Learning is not an intelligent robot that solves mathematical equations on a glass board! Image credit

Broadly, Machine Learning can be sub-categorized into four types:

1 — Supervised Learning

Given a set of labeled observations, find a function f which can be used to assign a class or value to unseen observations.

In supervised learning, we compare real labels with predicted labels. Predictions should be similar to real labels.

1.1 — Classification

Supervised Learning: Classification — Image Credit

In a classification problem, we are trying to predict results in a discrete output. In other words, we are trying to map input variables into discrete categories.