Clustering
Clustering is an unsupervised machine learning technique used to group similar data points together based on their features, without predefined labels. It identifies inherent patterns or structures in datasets by partitioning them into clusters where intra-cluster similarity is high and inter-cluster similarity is low. Common applications include customer segmentation, anomaly detection, and image compression.
Developers should learn clustering when dealing with unlabeled data to discover hidden patterns, such as in market research for customer grouping or in bioinformatics for gene expression analysis. It is essential for exploratory data analysis, dimensionality reduction, and preprocessing steps in data pipelines, particularly in fields like data science, AI, and big data analytics.