Matrix-Vector Multiplication
Matrix-Vector Multiplication is a fundamental operation in linear algebra and is widely used in data science and artificial intelligence. It involves multiplying a matrix with a vector to produce another vector. The matrix is a rectangular array of numbers, while the vector is a one-dimensional array of numbers. The number of columns in the matrix must be equal to the number of rows in the vector. The multiplication is performed by taking the dot product of each row of the matrix with the vector. The resulting vector is a linear combination of the columns of the matrix, where the coefficients are the elements of the vector. Matrix-Vector Multiplication is used in many applications, such as solving systems of linear equations, transforming coordinates in space, and performing linear regression.
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