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I want to learn machine learning methods, preferably high-performance methods, by R in the quickest way possible. I am totally familiar with R but very less experience with ML packages. I know some resources like books but what I intend by opening this topic is to find the quickest way possible. I also need to see some examples in the tutorial and I DO NOT need any theory.

TPArrow
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  • Regarding "I DO NOT need any theory": Learning how to operate ML packages without at least understanding best practice and common pitfalls due to your data problem, could lead you to waste a lot more time than if you had studied the theory in the first place. That is why most courses on the subject teach you the theory. ML "hacking" can get you quickly out of your depth. – Neil Slater Dec 09 '16 at 13:01
  • @NeilSlater, thank you for your reply. I know the theories and I just need to make myself familiar with the software. – TPArrow Dec 09 '16 at 14:01
  • What prevents you just using the reference documentation? That would be fast, and if you know the theory then you would quickly understand how the API relates to the theory (at least in my experience this is how I tackle work in Keras or TensorFlow, I'm not an expert at those libraries, but can usually find what I want very quickly). – Neil Slater Dec 09 '16 at 14:21

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There is the Wikibook Data Mining Algorithms In R and some useful examples at rdatamining.com

G5W
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