Question

Define the term clustering. Support your answer with a real life example.

Hint:

Clustering works best when you want to find natural groupings in large, unlabelled datasets.

Answer 1

Clustering is an unsupervised machine learning technique used to automatically group similar data points into clusters based on certain characteristics or patterns.
Unlike supervised learning, clustering does not require labelled data.
The main goal is to maximize similarity within clusters and minimize similarity between clusters.
It is a key tool in exploratory data analysis, helping to uncover hidden structures and relationships in datasets.
Clustering is widely used in data mining, market segmentation, image recognition, and anomaly detection.
Real Life Example:
An e-commerce company uses clustering to segment its customers into different groups based on purchase behavior.
Customers with similar buying patterns are grouped together.
This allows the company to design targeted marketing strategies, recommend relevant products, and improve customer satisfaction.
For example, frequent buyers of sports gear may receive special offers on new sports collections.
Clustering thus enables businesses to understand their audience better and make data-driven decisions.