Abstract Linear Algebra I
Projections are linear transformations that map a vector onto a subspace, resulting in a new vector that represents the closest point in that subspace. This concept is essential in understanding how vectors can be represented in terms of an orthonormal basis, allowing for easier calculations and simplifications in various mathematical contexts. Projections are often used in applications like least squares fitting and optimization problems, where minimizing distance to a subspace is crucial.
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