Lecture
This lecture introduces the concept of clustering, a method in unsupervised learning that separates data into sub-groups based on similarities. The instructor covers techniques such as hierarchical clustering, k-means, and density-based clustering, emphasizing the importance of evaluating clustering results and the practical applications in various fields like image analysis, market segmentation, and text clustering.