True title: The concept of basis in Machine Learning. Now, where did all the math go?

Those who have read machine learning text books or papers should probably know that they are quite often quite a hard read. It hard to wrap you head around and see the main points.

This is somehow unfortunate since most machine learning algorithms work more or less the same way. This is so, from linear regression, through support vector machine, through ada boost or decision trees those algorithms can be cast in the same framework.

Wheter images, text or time series, they work the same way. What is differerent in each case is THE BASIS.

The most natural machine learning algorithm: Nearest Neigbor or Similarity based prediction

A common framework for machine learning

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