Author: RicardoPublisher:
ISBN: 9780618445066
Category :
Languages : en
Pages :
Book Description
Ricardo Linear Algebra Ssm
Author: RicardoRicardo Linear Algebra
Author: RicardoLinear Algebra - Ssm
Author: PoolePublisher:
ISBN: 9780534390914
Category :
Languages : en
Pages :
Book Description
Contains worked solutions to odd-numbered exercises in the text, section-by-section study tips (definitions and concepts to master, skills to develop, links to later sections), and chapter review tests (short answer with solutions).
(WCS)Contemporary Linear Algebra with SSM & Study Tips set
Author: Howard AntonPublisher: Wiley
ISBN: 9780470039908
Category : Mathematics
Languages : en
Pages :
Book Description
Linear Algebra
Author: Donald H. PelletierPublisher:
ISBN: 9780835940641
Category : Algebras, Linear
Languages : en
Pages : 548
Book Description
Linear Algebra, Students Solutions Manual
Author: Terry LawsonPublisher: Wiley
ISBN: 9780471149545
Category : Mathematics
Languages : en
Pages : 112
Book Description
High level linear algebra book that blends both computational and theoretical aspects, using each to enhance the other. Explains the key points of the Gaussian elimination algorithm. Discusses vector spaces and linear transformations using matrix computations. Takes advantage of software packages such as MATLAB, Mathematica, and Maple.
Nakos Linear Algebra Ssm
Author: NakosLinear Algebra and Its Applications with R
Author: Ruriko YoshidaPublisher: CRC Press
ISBN: 1000400247
Category : Business & Economics
Languages : en
Pages : 424
Book Description
This book developed from the need to teach a linear algebra course to students focused on data science and bioinformatics programs. These students tend not to realize the importance of linear algebra in applied sciences, since traditional linear algebra courses tend to cover mathematical contexts but not the computational aspect of linear algebra or its applications to data science and bioinformatics. The author presents the topics in a traditional course, yet offers lectures as well as lab exercises on simulated and empirical data sets. This textbook provides students a theoretical basis which can then be applied to the practical R and Python problems, providing the tools needed for real-world applications. Each section starts with working examples to demonstrate how tools from linear algebra can help solve problems in applied sciences. These exercises start from easy computations, such as computing determinants of matrices, to practical applications on simulated and empirical data sets with R so that students learn how to get started with R, along with computational examples in each section, and then students learn how to apply what they've learned to problems in applied sciences. This book is designed from first principles to demonstrate the importance of linear algebra through working computational examples with R and Python, including tutorials on how to install R in the Appendix. If a student has never seen R, they can get started without any additional help. Since Python is one of the most popular languages in data science, optimization, and computer science, code supplements are available for students who feel more comfortable with Python. R is used primarily for computational examples to develop students’ practical computational skills. About the Author: Dr. Ruriko Yoshida is an Associate Professor of Operations Research at the Naval Postgraduate School. She received her PhD in Mathematics from the University of California, Davis. Her research topics cover a wide variety of areas: applications of algebraic combinatorics to statistical problems such as statistical learning on non-Euclidean spaces, sensor networks, phylogenetics, and phylogenomics. She teaches courses in statistics, stochastic models, probability, and data science.
Linear Algebra
Author: Jin Ho KwakPublisher:
ISBN: 9780817681951
Category :
Languages : en
Pages : 408
Book Description
Linear Algebra in Action
Author: Harry DymPublisher: American Mathematical Soc.
ISBN: 9780821838136
Category : Mathematics
Languages : en
Pages : 568
Book Description
Linear algebra permeates mathematics, perhaps more so than any other single subject. It plays an essential role in pure and applied mathematics, statistics, computer science, and many aspects of physics and engineering. This book conveys in a user-friendly way the basic and advanced techniques of linear algebra from the point of view of a working analyst. The techniques are illustrated by a wide sample of applications and examples that are chosen to highlight the tools of the trade. In short, this is material that the author wishes he had been taught as a graduate student. Roughly the first third of the book covers the basic material of a first course in linear algebra. The remaining chapters are devoted to applications drawn from vector calculus, numerical analysis, control theory, complex analysis, convexity and functional analysis. In particular, fixed point theorems, extremal problems, matrix equations, zero location and eigenvalue location problems, and matrices with nonnegative entries are discussed. Appendices on useful facts from analysis and supplementary information from complex function theory are also provided for the convenience of the reader. The book is suitable as a text or supplementary reference for a variety of courses on linear algebra and its applications, as well as for self-study.