Support Vector Machines (SVM)

From Week 7 of the lesson...
Didn't really get what is Support Vector Machines (SVM) initially so went to google up a bit and watch some videos. 

Summary:
  • It is a supervised learning models used to analysis regression or classification problems
  • Divide the classes of the data by a clear gap (aka "hyperplane") that is as wide as possible
  • Can be used to classify multi-dimensional data thus the classifier is known as "hyperplane"


Recommended Videos:

Support Vector Machine (SVM) - Fun and Easy Machine Learning (7 mins):
by Augmented Startups
https://www.youtube.com/watch?v=Y6RRHw9uN9o 


Support Vector Machines - The Math of Intelligence (Week 1) (30 mins);

by Siraj Raval

https://www.youtube.com/watch?v=g8D5YL6cOSE


Learning: Support Vector Machines (49 mins):

by MIT OpenCourseWare

https://www.youtube.com/watch?v=_PwhiWxHK8o



Also learnt about Gaussian Kernel...
  • It is used when there is a non-linear decision boundary 
  • If there is a small number of features but large amount of data, use SVM with Gaussian kernel 
  • Perform feature scaling before using Gaussian kernel

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