Vector projection is used in the important statistical problem of linear regression, as well as in principal component analysis, one of the most used methods in data science.
Here, one is confronted with the task of representing many, possibly high-dimensional, data points within a space of lower dimensionality in such a way that there is as minimal information loss as possible.
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