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Clustering for Machine Learning

Clustering has wide application in business analytics and in machine learning. Find out more about this powerful technique in this on-demand webinar featuring Ilknur Kaynar Kabul, PhD, Senior Manager in Advanced Analytics R&D at SAS.

Kabul helps analysts gain familiarity with multiple clustering algorithms and better understand how to apply the most relevant technique per business need.

Discussion includes:

• When to use clustering techniques in general, and which algorithms are best for solving specific business problems.


• How to use clustering for missing value imputation and anomaly detection.


• How to use clustering for segmentation/customer profiling.
Recorded Dec 18 2015 23 mins
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Presented by
Ilknur Kaynar Kabul, PhD, Senior Manager in Advanced Analytics R&D at SAS.
Presentation preview: Clustering for Machine Learning

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In today's organizations, you need to get relevant data quickly to drive faster business decisions. With big data, sometimes that's easier said than done.

SAS® Business Intelligence offers predictive insights with the ability to understand the past, monitor the present and predict outcomes, no matter the size or complexity of your data. In fact, SAS helps you deliver accurate, valuable information – from Hadoop or any other big data source.

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One of the key components of SAS Business Intelligence, SAS Visual Analytics, offers self-service data discovery, enabling even nontechnical business users to explore billions of rows of data in seconds. With this tool, you can discover more opportunities and make more precise decisions, easily publishing reports to the Web and mobile devices.

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  • Title: Clustering for Machine Learning
  • Live at: Dec 18 2015 10:05 pm
  • Presented by: Ilknur Kaynar Kabul, PhD, Senior Manager in Advanced Analytics R&D at SAS.
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