Beginner · Fundamentals

Supervised Machine Learning

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. A subset of ML where models learn from labeled data to predict outcomes.

Technical Definition

A subset of ML where models learn from labeled data to predict outcomes.

How it works

Supervised Machine Learning is a training method where algorithms infer a function from labeled training data. Each piece of training data consists of an input and an expected, correct output. The model's goal is to learn how to map new inputs to correct outputs. This paradigm is common in tasks like image classification and spam detection.

Related Concepts

• Regression — A supervised learning task that predicts a continuous numeric value.
• Unsupervised Learning — Learning patterns from data that has no labels — only the inputs.