SVM Regression, prediction and losses
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SVM Regression, prediction and losses

Highlights

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.

About the Course Provider

Coursera provides access to more than 3000+ courses across a wide variety of subjects in parntership with different universities and organizations.

Course by

  • self
    Self paced
  • dueration
    Duration 2 hours
  • domain
    Domain Personal Development
  • subs
    Monthly Subscription Option not available
  • fee
    Buy Now Free
  • language
    Language English