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Linear algebra has been one of the most reliable tools in solving daily human challenges. A case in point is machine learning techniques that are mostly drawn from linear algebra. In this text, we introduce the reader to linear algebra and slowly advance their skills in the subject. From vector space structure, systems of linear equations, matrices, determinants, linear t transformations, similarity, diagnolization, minimal polynomials, spectral properties of matrices, singular value decomposition to linear functionals, we have deeply elaborated the practical uses of these notions. Inner…mehr

Produktbeschreibung
Linear algebra has been one of the most reliable tools in solving daily human challenges. A case in point is machine learning techniques that are mostly drawn from linear algebra. In this text, we introduce the reader to linear algebra and slowly advance their skills in the subject. From vector space structure, systems of linear equations, matrices, determinants, linear t transformations, similarity, diagnolization, minimal polynomials, spectral properties of matrices, singular value decomposition to linear functionals, we have deeply elaborated the practical uses of these notions. Inner products and bilinear quadratic forms have also been discussed in the book. This book intended to build confidence and skills are far a linear algebra in concerned. We have also illustrated solutions to selected problems.
Autorenporträt
Joseph is a second year PhD student of Pure Mathematics at Jaramogi Oginga Odinga University of Science and Technology and a Tutorial Fellow of Pure Mathematics at Technical University of Kenya.