Vector Space
In data science, a vector space is a mathematical structure that consists of a set of vectors, which can be added together and multiplied by scalars (usually real numbers). Vector spaces are used to represent data in a way that allows for mathematical operations to be performed on them. In machine learning, vector spaces are often used to represent features of data points, where each feature is a dimension in the vector space. For example, a dataset of images can be represented as a set of vectors, where each vector represents an image and each dimension represents a pixel value. Vector spaces are also used in natural language processing to represent words as vectors, where each dimension represents a different aspect of the word's meaning or context.
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