| Description |
1 online resource (1 streaming video file (36 min., 46 sec.)) |
| Summary |
"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 |
| Notes |
Title from title screen (viewed September 26, 2017) |
|
"Part 4 of 6." |
|
Date of publication taken from resource description page |
| Performer |
Presenters, Alessandra Staglianò, Angie Ma, and Gary Willis |
| Subject |
Regression analysis.
|
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Machine learning.
|
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Hierarchical clustering (Cluster analysis)
|
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Artificial intelligence.
|
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Regression Analysis
|
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Artificial Intelligence
|
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artificial intelligence.
|
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Artificial intelligence.
|
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Hierarchical clustering (Cluster analysis)
|
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Machine learning.
|
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Regression analysis.
|
| Form |
Streaming video
|
| Author |
Ma, Angie, speaker
|
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Willis, Gary, speaker
|
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