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Support Vector Machine Implementation Through PAI
Support Vector Machine Implementation Through PAI
Clouder at a Glance
  • Video Course Duration
    44 Minutes
  • Exam Questions
    15 Questions
  • No. of Exam Attempts
    2 Times
  • Available Languages
    English
USD 10.00
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.
Exam Overview
  • Certification:
    Apsara Clouder - Big Data: Support Vector Machine Implementation Through PAI
  • Duration:
    30 Minutes
  • Type:
    Online
  • Available Languages:
    English
  • Registration Fee:
    USD 10.00
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.
Show Details
  • Index
  • SVM (Support Vector Machine) — TheoryⅠ
  • SVM (Support Vector Machine) — TheoryⅡ
  • SVM (Support Vector Machine)— Application Demo on PAI
  • Recap
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