Clustering is a fundamental technique in unsupervised machine learning that involves grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar to each other than to those in other groups (clusters). The goal is to uncover the inherent structure in data without using pre-labeled responses.
- Customer Segmentation: Identifying distinct groups of customers based on purchasing behavior.
- Image Segmentation: Dividing an image into segments for analysis.
- Anomaly Detection: Identifying unusual data points in a dataset.
- Biological Data Analysis: Grouping genes or proteins with similar expression patterns.
This repository aims to provide an overview of various clustering methods, along with practical examples and implementations.