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Clustering Techniques and Use Cases by preetysharma05031 is a document available to read on EtoBox.

Clustering is an unsupervised machine learning technique that groups similar data points into clusters without requiring labeled data. Various algorithms such as K-Means, Hierarchical, and DBSCAN are used for clustering, each with unique applications like customer segmentation, anomaly detection, and image processing. The choice of algorithm depends on the data characteristics and specific use cases.

Author
preetysharma05031
Language
EN