Short piece that addresses typical techniques. But it is not all about technique, it is how the technique is connected to the data from the domain of the problem, and ultimately connected to a real world decision.
" ... In this post we will first look at some well known and understood examples of machine learning problems in the real world. We will then look at a taxonomy (naming system) for standard machine learning problems and learn how to identify a problem as one of these standard cases. This is valuable, because knowing the type of problem we are facing allows us to think about the data we need and the types of algorithms to try. ... "
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