What’s clustering? How to organize your room?

Another example:

In summary, clustering is a machine learning technique used to group similar data points together.

More examples of clustering:

1. Customer Segmentation: Businesses use clustering to group customers based on their purchasing behavior, demographics, or preferences. For example, customers could be grouped into clusters like “budget shoppers,” “luxury buyers,” or “frequent buyers” for targeted marketing.
2. Image Segmentation: In computer vision, clustering is used to partition an image into regions with similar pixel values, helping to identify objects or areas in an image, such as grouping pixels by color or texture.
3. Document Clustering: Clustering is applied to large sets of documents, like news articles or research papers, to organize them into topics or themes. For example, clustering news articles can group them into categories like “sports,” “politics,” or “technology.”
4. Anomaly Detection: In cybersecurity, clustering helps detect unusual behavior by grouping normal data and identifying outliers. For example, clustering network activity can help detect an unusual spike in traffic, which might indicate a security breach.
5. Social Network Analysis: Clustering can be used to identify communities within a social network, such as grouping people based on their social connections or common interests (e.g., finding groups of people who frequently interact on Twitter or Facebook).