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Cluster Analysis: K-Means and Hierarchical

Cluster analysis is an extremely important set of techniques to determine groups with similar characteristics.

Often cluster analysis is used to determine similar groups for marketing products. This is called market segmentation.

In this excellent video, Luis Serrano, Quantum Artificial Intelligence Research Scientist, introduces the two of the most common methods for splitting data into meaningful groups or clusters: K-means and hierarchical grouping.

After suggesting how a human might do it, he translates the method into how the computer would do it using simple examples: locating a pizza parlor. 

Here is his YouTube channel where you can find more excellent videos on machine learning and math.

Luis also runs Serrano Academy which focuses on artificial intelligence and math made easy. 

For those of you who want to learn more about machine learning, Mr. Serrano also has a new book Grokking Machine Learning. This is a book in which he explains the main algorithms and techniques of supervised learning in a very friendly and intuitive way that doesn’t require heavy mathematics or coding.

Luis earned in Ph.D. in mathematics from the University of Michigan.

For those who use Minitab 18, this link gives an overview of the two methods discussed in the video and when to use each.

 

2020-05-16T07:40:12+00:00 By Endrea Kosven|Tags: , , , |0 Comments

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