AI Glossary Term

What does “Unsupervised Learning” mean?

Definition

Learning patterns from unlabeled data without explicit target outputs.

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How Unsupervised Learning works

Example

A retailer feeds purchase histories into a clustering algorithm that has no labels. It finds groups of similar shoppers, and analysts then examine each group to decide what to call it.

Why it matters

Most data has no labels, so methods that find structure on their own are valuable. Results need human interpretation.

Common questions

Common tasks?

Clustering, dimensionality reduction, and anomaly detection.

How do I know it is right?

There is no answer key, so you check whether results are stable and useful for your goal.

Unsupervised vs self-supervised?

Self-supervised builds its own prediction task from the data to learn features.

Continual LearningTraining approaches that let a model keep learning from new data without forgetting prior knowledge.Data LabelingThe process of assigning tags or target outputs to raw data for supervised learning.Machine Learning (ML)Methods that allow systems to learn patterns from data and improve over time.Self-Supervised LearningLearning representations from unlabeled data by predicting masked or transformed parts.Algorithmic BiasSystematic unfairness in model outputs caused by skewed data, assumptions, or modeling choices.In-Context LearningA model's ability to follow patterns from examples provided directly in the prompt.

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