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Hands-on unsupervised learning with Python

Author: Stefan Jansen
Publisher: [Place of publication not identified] : Packt, [2018]
Edition/Format:   eVideo : Clipart/images/graphics : EnglishView all editions and formats
Summary:
"This course explains the most important Unsupervised Learning algorithms using real-world examples of business applications in Python code. This course will allow you to utilize Principal Component Analysis, and to visualize and interpret the results of your datasets such as the ones in the above description. You will also be able to apply hard and soft clustering methods (k-Means and Gaussian Mixture Models) to  Read more...
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Details

Material Type: Clipart/images/graphics, Internet resource, Videorecording
Document Type: Internet Resource, Computer File, Visual material
All Authors / Contributors: Stefan Jansen
OCLC Number: 1048573670
Notes: Title from title screen (viewed August 9, 2018).
Date of publication from resource description page.
Performer(s): Presenter, Stefan Jansen.
Description: 1 online resource (1 streaming video file (3 hr., 34 min., 24 sec.)) : digital, sound, color
Responsibility: Stefan Jansen.

Abstract:

"This course explains the most important Unsupervised Learning algorithms using real-world examples of business applications in Python code. This course will allow you to utilize Principal Component Analysis, and to visualize and interpret the results of your datasets such as the ones in the above description. You will also be able to apply hard and soft clustering methods (k-Means and Gaussian Mixture Models) to assign segment labels to customers categorized in your sample data sets."--Resource description page.

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