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Clustering and Unsupervised Learning
註釋"This course introduces clustering, a common technique used widely in unsupervised machine learning. The course begins by defining what clustering means through graphical explanations, and describes the common applications of clustering. Next, it explores k-means clustering in detail, including the concepts of distance functions and k-modes; illustrates hierarchical clustering through visual examples of dendrograms, and discusses different types of clustering algorithms. The course ends with a comparison of the performance of different algorithms. An understanding of basic algebra is required and some knowledge of linear algebra will be helpful."--Resource description page.