SVM Regression, prediction and losses

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SVM Regression, prediction and losses provided by Coursera is a comprehensive online course, which lasts for 2 hours worth of material. SVM Regression, prediction and losses is taught by Ashish Dikshit. Upon completion of the course, you can receive an e-certificate from Coursera. The course is taught in Englishand is Paid Course. Visit the course page at Coursera for detailed price information.

Overview
  • In this 1-hour long project-based course, you will learn how to
    Train SVM regression model- with large & small margin, second degree polynomial kernel, make prediction using Linear SVM classifier; how a small weight vector results in a large margin? and finally
    pictorial representation for Hinge loss. This project gives you easy access to the invaluable learning techniques used by experts in machine learning.
    Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your understanding to thoroughness in machine learning.