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Opiniones y comentarios de aprendices correspondientes a Cluster Analysis in Data Mining por parte de Universidad de Illinois en Urbana-Champaign

4.4
234 calificaciones
40 revisiones

Acerca del Curso

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....

Principales revisiones

ES

Dec 18, 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.

DD

Sep 25, 2017

A very good course, it gives me a general idea of how clustering algorithm work.

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