<ul><li>Unsupervised learning, specifically clustering, reveals hidden patterns in data without predefined categories or targets.</li><li>Clustering algorithms group data points based on similarities, with popular techniques like K-means, hierarchical clustering, and DBSCAN.</li><li>Significance of clustering includes discovering patterns, reducing data dimensionality, improving data understanding, and enabling anomaly detection.</li><li>Applications range from customer segmentation to image and document clustering, with challenges including determining optimal clusters and addressing biases.</li></ul>

Unsupervised Learning: Unveiling Hidden Patterns Through Clustering

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