Detailed explanation
The model looks for groupings (clustering), dimensionality reduction (PCA), patterns or anomalies. Very useful for data exploration, customer segmentation, fraud detection or pre-training.
Examples
Customer segmentation
Network anomaly detection
Dimensionality reduction for visualization
Frequently asked questions
Are the results always reliable?
Discovered structures always need business interpretation and validation.
Related terms
Machine Learning
A branch of AI where models learn patterns from data instead of following explicit rules.
Supervised Learning
Learning from labeled examples (input → expected output).
Embedding
An embedding is a numerical vector representation of text, image, or audio data that captures its semantic meaning, enabling similarity search and machine learning on unstructured content.
Reinforcement Learning
A learning method where an agent learns to act by trial and error, maximizing a reward.
Last updated: 7/15/2026