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Anomaly detection for data science

Author: Zacharias Voulgaris
Publisher: [Place of publication not identified] : [Technics Publications], [2018]
Edition/Format:   eVideo : Clipart/images/graphics : English
Summary:
"Explore the ins and outs of anomaly detection, and learn the various methods for performing it within data science. We’ll look at how it applies to various data science scenarios, and how it can bring about value to an organization. We’ll close with an overview of the various programming resources for this technique for the Python language, and some considerations to have in mind when identifying and handling  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: Zacharias Voulgaris
OCLC Number: 1032263908
Notes: Title from title screen (viewed April 19, 2018).
Imprint from resource description page.
Performer(s): Presenter, Zacharias Voulgaris.
Description: 1 online resource (1 streaming video file (18 min., 5 sec.)) : digital, sound, color
Responsibility: Zacharias Voulgaris.

Abstract:

"Explore the ins and outs of anomaly detection, and learn the various methods for performing it within data science. We’ll look at how it applies to various data science scenarios, and how it can bring about value to an organization. We’ll close with an overview of the various programming resources for this technique for the Python language, and some considerations to have in mind when identifying and handling anomalies in a dataset."--Resource description page.

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