Introduces ordinary differential equations, systems of linear equations, matrices, determinants, vector spaces, linear transformations, and systems of linear differential equations. Prereq., APPM 1360 ...

How much math knowledge do you need for machine learning and deep learning? Some people say not much. Others say a lot. Both are correct, depending on what you want to achieve. There are plenty of ...

Vector spaces, linear transformation, matrix representation, inner product spaces, isometries, least squares, generalised inverse, eigen theory, quadratic forms, norms, numerical methods. The fourth ...

N. E. Gretsky and J. J. Uhl, Jr. Representations of bounded linear operators on Banach function spaces of vector-valued functions to Banach spaces are given in terms of operator-valued measures. Then ...

Two vectors of information are needed to produce the optimally scaled variable: the initial variable scaling vector x and the target vector y. For convenience, both vectors are first sorted on the ...

THIS most welcome treatise fills a serious gap in English mathematical literature. It provides for the first time a comprehensive account of the general transformation theory which steadily dominates ...