Unsupervised Learning
Unsupervised learning involves algorithms that analyze data without labeled responses. Common algorithms include clustering and dimensionality reduction. Applications range from customer segmentation to anomaly detection. Challenges include evaluating results without labels and interpreting complex patterns, but it remains crucial for uncovering insights from unstructured data.