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.
This training is for people who have machine learning and database experience.
How to get Certified
Certification:Apsara Clouder - Big Data: Support Vector Machine Implementation Through PAI
Exam Duration:30 Minutes
No. of Exam Attempts:2 Times
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.
- SVM (Support Vector Machine) — TheoryⅠ
- SVM (Support Vector Machine) — TheoryⅡ
- SVM (Support Vector Machine)— Application Demo on PAI