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| Author | : Stephen Boyd |
| Publisher | : Cambridge University Press |
| Total Pages | : 477 |
| Release | : 2018-06-07 |
| Genre | : Business & Economics |
| ISBN | : 1316518965 |
A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
| Author | : Jacob T. Schwartz |
| Publisher | : Courier Corporation |
| Total Pages | : 198 |
| Release | : 2012-05-23 |
| Genre | : Mathematics |
| ISBN | : 0486143708 |
Realizing that matrices can be a confusing topic for the beginner, the author of this undergraduate text has made things as clear as possible by focusing on problem solving, rather than elaborate proofs. He begins with the basics, offering students a solid foundation for the later chapters on using special matrices to solve problems.The first three chapters present the basics of matrices, including addition, multiplication, and division, and give solid practice in the areas of matrix manipulation where the laws of algebra do not apply. In later chapters the author introduces vectors and shows how to use vectors and matrices to solve systems of linear equations. He also covers special matrices — including complex numbers, quaternion matrices, and matrices with complex entries — and transpose matrices; the trace of a matrix; the cross product of matrices; eigenvalues and eigenvectors; and infinite series of matrices. Exercises at the end of each section give students further practice in problem solving. Prerequisites include a background in algebra, and in the later chapters, a knowledge of solid geometry. The book was designed as an introductory text for college freshmen and sophomores, but selected chapters can also be used to supplement advanced high school classes. Professionals who need a better understanding or review of the subject will also benefit from this concise guide.
| Author | : K.T. Leung |
| Publisher | : Hong Kong University Press |
| Total Pages | : 357 |
| Release | : 1994-08-01 |
| Genre | : Mathematics |
| ISBN | : 9622093604 |
This book is the last volume of a three-book series written for Sixth Form students and first-year undergraduates. It introduces the important concepts of finite-dimensional vector spaces through the careful study of Euclidean geometry. In turn, methods of linear algebra are then used in the study of coordinate transformations through which a complete classification of conic sections and quadric surfaces is obtained. The book concludes with a detailed treatment of linear equations in n variables in the language of vectors and matrices. Illustrative examples are included in the main text and numerous exercises are given in each section. The other books in the series are Fundamental Concepts of Mathematics (published 1988) and Polynomials and Equations (published 1992).
| Author | : Richard Cotton |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 250 |
| Release | : 2013-09-09 |
| Genre | : Computers |
| ISBN | : 1449357180 |
Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, youâ??ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what youâ??ve learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code
| Author | : Chris Albon |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 305 |
| Release | : 2018-03-09 |
| Genre | : Computers |
| ISBN | : 1491989335 |
This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications. You’ll find recipes for: Vectors, matrices, and arrays Handling numerical and categorical data, text, images, and dates and times Dimensionality reduction using feature extraction or feature selection Model evaluation and selection Linear and logical regression, trees and forests, and k-nearest neighbors Support vector machines (SVM), naïve Bayes, clustering, and neural networks Saving and loading trained models
| Author | : Michael Mortenson |
| Publisher | : Industrial Press |
| Total Pages | : 350 |
| Release | : 2020-04-15 |
| Genre | : Technology & Engineering |
| ISBN | : 9780831136550 |
| Author | : Alan Tucker |
| Publisher | : Macmillan College |
| Total Pages | : 472 |
| Release | : 1993 |
| Genre | : Mathematics |
| ISBN | : |
Covers the fundamental role of linear algebra with both pure and applied mathematics as well as client disciplines such as engineering, the physical sciences and economics. This text examines the interrelationships amongst theory, computation and applications.
| Author | : Dennis S. Bernstein |
| Publisher | : Princeton University Press |
| Total Pages | : 1593 |
| Release | : 2018-02-27 |
| Genre | : Mathematics |
| ISBN | : 0691176531 |
The essential reference book on matrices—now fully updated and expanded, with new material on scalar and vector mathematics Since its initial publication, this book has become the essential reference for users of matrices in all branches of engineering, science, and applied mathematics. In this revised and expanded edition, Dennis Bernstein combines extensive material on scalar and vector mathematics with the latest results in matrix theory to make this the most comprehensive, current, and easy-to-use book on the subject. Each chapter describes relevant theoretical background followed by specialized results. Hundreds of identities, inequalities, and facts are stated clearly and rigorously, with cross-references, citations to the literature, and helpful comments. Beginning with preliminaries on sets, logic, relations, and functions, this unique compendium covers all the major topics in matrix theory, such as transformations and decompositions, polynomial matrices, generalized inverses, and norms. Additional topics include graphs, groups, convex functions, polynomials, and linear systems. The book also features a wealth of new material on scalar inequalities, geometry, combinatorics, series, integrals, and more. Now more comprehensive than ever, Scalar, Vector, and Matrix Mathematics includes a detailed list of symbols, a summary of notation and conventions, an extensive bibliography and author index with page references, and an exhaustive subject index. Fully updated and expanded with new material on scalar and vector mathematics Covers the latest results in matrix theory Provides a list of symbols and a summary of conventions for easy and precise use Includes an extensive bibliography with back-referencing plus an author index
| Author | : Dwight E. Neuenschwander |
| Publisher | : JHU Press |
| Total Pages | : 244 |
| Release | : 2015 |
| Genre | : Mathematics |
| ISBN | : 142141564X |
It is an ideal companion for courses such as mathematical methods of physics, classical mechanics, electricity and magnetism, and relativity.--Gary White, editor of The Physics Teacher "American Journal of Physics"
| Author | : Stanton A. Glantz |
| Publisher | : McGraw Hill Professional |
| Total Pages | : 1212 |
| Release | : 2016-02-22 |
| Genre | : Medical |
| ISBN | : 0071822445 |
A textbook on the use of advanced statistical methods in healthcare sciences Primer of Applied Regression & Analysis of Variance is a textbook especially created for medical, public health, and social and environmental science students who need applied (not theoretical) training in the use of statistical methods. The book has been acclaimed for its user-friendly style that makes complicated material understandable to readers who do not have an extensive math background. The text is packed with learning aids that include chapter-ending summaries and end-of-chapter problems that quickly assess mastery of the material. Examples from biological and health sciences are included to clarify and illustrate key points. The techniques discussed apply to a wide range of disciplines, including social and behavioral science as well as health and life sciences. Typical courses that would use this text include those that cover multiple linear regression and ANOVA. Four completely new chapters Completely updated software information and examples
