AI Reference 029 Classical AI & Machine Learning Wikipedia guided Primary sources linked

Unsupervised Learning

Definition

Supervised learning trains a model from examples paired with known labels or target values. Classification and regression are common supervised tasks.

What is unsupervised learning?

Unsupervised learning works with data that does not come with explicit target labels. The goal is to discover structure, representations or regularities in the data itself.

Common tasks

Clustering groups similar items; dimensionality-reduction methods compress data into fewer variables; representation-learning systems learn useful internal features. Principal component analysis and k-means clustering are classic examples, while autoencoders are a neural approach.

How it differs from supervised learning

In supervised learning, the desired output is supplied. In unsupervised learning, the system must identify structure without a provided answer key. Self-supervised learning is related but creates prediction targets from the data itself and has become especially important in modern foundation-model training.

Related terms, defined

Classical AI & Machine Learning Artificial Intelligence vs Machine Learning Artificial intelligence is the broader field concerned with systems performing tasks associated with intelligent behavior; machine learning is a major subfield in which systems learn patterns from data. Classical AI & Machine Learning Symbolic AI Symbolic AI represents knowledge with explicit symbols, rules and structures, then manipulates those representations with logic, search or planning procedures. Classical AI & Machine Learning Search Algorithms in Artificial Intelligence AI search algorithms explore possible states or actions in order to find paths, plans or solutions. Classical examples include breadth-first search, depth-first search and A*. Classical AI & Machine Learning Heuristics and Problem Solving A heuristic is an estimate or rule used to guide search toward promising states without exhaustively checking every alternative. Classical AI & Machine Learning Knowledge Representation Knowledge representation studies how facts, relations, rules and concepts can be encoded so a computer system can reason over them.

Reference guide and primary sources

Wikipedia is used here as a terminology and history reference guide. Current model versions, institutional statistics and product-specific claims are also linked to first-party or institutional sources because those details can change faster than encyclopedia articles.

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