Machine Learning
beginner
Unsupervised Learning
Training a model on unlabeled data to find patterns or structure.
Detailed Explanation
Unsupervised learning is a type of machine learning where the algorithm learns patterns from unlabeled data. Unlike supervised learning, there are no correct answers and no teacher. The goal is to model the underlying structure or distribution in the data to learn more about it. Common unsupervised learning tasks include clustering (grouping similar instances), dimensionality reduction, and anomaly detection.
Examples
- Customer segmentation
- Feature extraction
- Anomaly detection in network traffic
Tags
unlabeled data
clustering
dimensionality reduction