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Learner Reviews & Feedback for Cluster Analysis in Data Mining by University of Illinois Urbana-Champaign
408 ratings
About the Course
Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications.
Top reviews
ES
Dec 17, 2018
This was my favorite course in the whole specialization. Everything is explained very concisely and clearly making the subject matter very easy to understand.
GV
Sep 18, 2017
Very informative lectures, wonderful assignments. This course isn't so easy but it gives you real knowledge and useful experience.
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