Vector Spaces
In data science, a vector space is a mathematical structure consisting of a set of vectors that can be added together and multiplied (scaled) by numbers, called scalars. Vector spaces are used to represent data in a way that allows for mathematical operations such as addition, subtraction, and multiplication to be performed on the data. In machine learning, vector spaces are often used to represent features of data, such as the pixel values in an image or the frequency of words in a text document. By representing data in a vector space, machine learning algorithms can more easily find patterns and relationships in the data.
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