Introduction
						SVM (Support Vector Machine) is among the best “off-the-shelf” supervised learning algorithms which can be used for both regression and classification tasks. It is widely used in classification objectives. A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples. In two dimentional space this hyperplane is a line dividing a plane in two parts where in each class lay in either side. This course  introduces the basic concepts of SVM as well as how to use Alibaba Cloud Machine Learning Platform for AI to apply SVM.
					Recommended For
						This training is for people who have machine learning  and database experience.
					How to get Certified
						
					Exam Overview
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								Certification:Apsara Clouder - Big Data: Support Vector Machine Implementation Through PAI
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								Exam Type:Online
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								Available Languages:English
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								Exam Duration:30 Minutes
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								No. of Exam Attempts:2 Times
Courses
						Support Vector Machine Implementation Through PAI
								Through this course, you will learn what is SVM  (Support Vector Machine), and how to use Alibaba Cloud Machine Learning Platform for AI to implement SVM.
								
								
							- Index 
- SVM (Support Vector Machine) — TheoryⅠ 
- SVM (Support Vector Machine) — TheoryⅡ 
- SVM (Support Vector Machine)— Application Demo on PAI 
- Recap 
 
				
			 
          