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Description	SVM are known to be difficult to grasp. This tutorial series is intended to give you all the necessary tools to really understand the math behind
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SVM Tutorial Menu Menu Support Vector Machines Tutorial Understanding Support Vector Machines SVM are known to be difficult to grasp. Many people refer to them as "black box". This tutorial series is intended to give you all the necessary tools to really understand the math behind SVM. It starts softly and then get more complicated. But my goal here is to keep everybody on board , especially people who do not have a strong mathematical background. Read the Support Vector Machine tutorial If you wish to have an overview of what SVMs are, you can read this article An overview of Support Vector Machines SVM R tutorials R is a good language if you want to experiment with SVM. So I wrote some introductory tutorials about it. The article about Support Vector Regression might interest you even if you don’t use R. How to classify text in R ? Support Vector Regression with R Text classification tutorials You can apply SVM to a wide variety of subjects. One of them is text classification. In

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