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.
About this Course
Skills you will gain
- 5 stars66.33%
- 4 stars23.36%
- 3 stars5.77%
- 2 stars2.01%
- 1 star2.51%
TOP REVIEWS FROM CLUSTER ANALYSIS IN DATA MINING
Good course for understanding the Cluster Analysis & Algorithms, instructor is very experienced and well explained, thanks
Awesome !!! Great course about clustering analysis.
Covers great deal of topics and various aspects of clustering
it was a really good experience. this course has given me good exposure to data mining
About the Data Mining Specialization
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