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[Solved]: Can we understand SVM without knowledge of Machine Learning

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Problem Detail: 

I was told by my adviser (future one) to look into libsvm library or any other and try to get familiar with it.. to work on a programming project (on Machine Learning) (will start in a month).

my background: Programming knowledge in Python, C.. doing Java now.

So, where should I probably start? and How long it takes me to get into ML, SVM etc.. and be productive? Would I probably fit for this project? --considering my programming background (I so far have been much into Web development, wanted to take a change and have fun)

Asked By : Iamcool

Answered By : Peter

I don't think there is anything that should stop you. A couple of tips to set you on the right path:

  • The basic principles of Machine Learning are very simple. They are often formalized in a way that makes it look very complicated, but this is only necessary if you want to get into the details of why things work. The general framework of what makes a classifier or what makes a clustering algorithm is very simple. Make sure you understand things on that level, before you dig into the details.
  • The title question (can SVMs be understood without ML knowledge) is slightly non-sensical. Understanding the basic ideas of ML is a minor investment and understanding SMVs takes much longer. There's no reason not to get a basic idea of what machine learning is before you dig into SVMs.
  • Make sure you have a good intuitive undertanding of the following principles and distinctions: features and instances, clustering and classification, supervised and unsupervised learning. After that, SVMs are just one particular way of solving a particular problem.
  • If you understand what a classifier is, you can start using SVMs without knowing anything about how they work or what they do. This may not give you the best result, but it's a good way to start learning by doing.

I can't really give you any references to start reading, since most of what's out there is far to formal for the level you'd want to start with. I recommend browsing around. If something is easy to read, then continue on, if it's too full of math, try something else first.

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Question Source : http://cs.stackexchange.com/questions/11854

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