Unsupervised Learning Definition

Unsupervised Learning Definition

Unsupervised learning is a type of machine learning services that works with unlabelled data. This means that unsupervised learning doesn’t require any predefined categories or labels to learn from the data. In contrast, supervised learning methods work with labeled data. The key aspect of unsupervised learning is that it can identify hidden patterns and relationships in raw, unprocessed data autonomously. It’s like giving an algorithm a complex puzzle without the picture on the box; the algorithm must discern structure, patterns, and relationships entirely on its own.

In unsupervised learning, the algorithm sorts through data looking for patterns or groupings. It’s particularly good at clustering and association tasks. For example, an unsupervised learning algorithm can scan millions of social media posts and group them into different categories based on content, tone, or user demographics. This is a prime example of the practical application of the definition of unsupervised learning.