Mathematics Foundation Course: Linear algebra (I)
Author : Open University. Mathematics Foundation Course Team
Publisher :
Page : 66 pages
File Size : 33,90 MB
Release : 1971
Category : Mathematics
ISBN :
Author : Open University. Mathematics Foundation Course Team
Publisher :
Page : 66 pages
File Size : 33,90 MB
Release : 1971
Category : Mathematics
ISBN :
Author : Sheldon Axler
Publisher : Springer Science & Business Media
Page : 276 pages
File Size : 21,80 MB
Release : 1997-07-18
Category : Mathematics
ISBN : 9780387982595
This text for a second course in linear algebra, aimed at math majors and graduates, adopts a novel approach by banishing determinants to the end of the book and focusing on understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space has an eigenvalue. The book starts by discussing vector spaces, linear independence, span, basics, and dimension. Students are introduced to inner-product spaces in the first half of the book and shortly thereafter to the finite- dimensional spectral theorem. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition features new chapters on diagonal matrices, on linear functionals and adjoints, and on the spectral theorem; some sections, such as those on self-adjoint and normal operators, have been entirely rewritten; and hundreds of minor improvements have been made throughout the text.
Author : Ivan Savov
Publisher :
Page : 596 pages
File Size : 40,25 MB
Release : 2020-10-25
Category : MATHEMATICS
ISBN : 9780992001025
This textbook covers the material for an undergraduate linear algebra course: vectors, matrices, linear transformations, computational techniques, geometric constructions, and theoretical foundations. The explanations are given in an informal conversational tone. The book also contains 100+ problems and exercises with answers and solutions. A special feature of this textbook is the prerequisites chapter that covers topics from high school math, which are necessary for learning linear algebra. The presence of this chapter makes the book suitable for beginners and the general audience-readers need not be math experts to read this book. Another unique aspect of the book are the applications chapters (Ch 7, 8, and 9) that discuss applications of linear algebra to engineering, computer science, economics, chemistry, machine learning, and even quantum mechanics.
Author : Jeff Suzuki
Publisher : Johns Hopkins University Press
Page : 296 pages
File Size : 36,58 MB
Release : 2018-12-14
Category : Mathematics
ISBN : 1421427052
Uncovers the surprising ways math shapes our lives—from whom we date to what we learn. How do dating sites match compatible partners? What do cell phones and sea coasts have in common? And why do computer scientists keep ant colonies? Jeff Suzuki answers these questions and more in Patently Mathematical, which explores the mathematics behind some of the key inventions that have changed our world. In recent years, patents based on mathematics have been issued by the thousands—from search engines and image recognition technology to educational software and LEGO designs. Suzuki delves into the details of cutting-edge devices, programs, and products to show how even the simplest mathematical principles can be turned into patentable ideas worth billions of dollars. Readers will discover • whether secure credit cards are really secure • how improved data compression made streaming video services like Netflix a hit • the mathematics behind self-correcting golf balls • why Google is such an effective and popular search engine • how eHarmony and Match.com find the perfect partner for those seeking a mate • and much more! A gifted writer who combines quirky historical anecdotes with relatable, everyday examples, Suzuki makes math interesting for everyone who likes to ponder the world of numerical relationships. Praise for Jeff Suzuki's Constitutional Calculus "Presents an entertaining and insightful approach to the mathematics that underlies the American system of government. The book is neatly organized, breaking down the United States Constitution by article, section, and amendment. Within each piece, Suzuki reviews the mathematical principles that went into the underlying framework."—Mathematical Reviews "A breath of fresh air. . . . A reaffirmation that mathematics should be used more often to make general public policy."—MAA Reviews
Author : Kenneth Kuttler
Publisher :
Page : 586 pages
File Size : 11,27 MB
Release : 2020
Category : Algebras, Linear
ISBN :
"A First Course in Linear Algebra, originally by K. Kuttler, has been redesigned by the Lyryx editorial team as a first course for the general students who have an understanding of basic high school algebra and intend to be users of linear algebra methods in their profession, from business & economics to science students. All major topics of linear algebra are available in detail, as well as justifications of important results. In addition, connections to topics covered in advanced courses are introduced. The textbook is designed in a modular fashion to maximize flexibility and facilitate adaptation to a given course outline and student profile. Each chapter begins with a list of student learning outcomes, and examples and diagrams are given throughout the text to reinforce ideas and provide guidance on how to approach various problems. Suggested exercises are included at the end of each section, with selected answers at the end of the textbook."--BCcampus website.
Author : Marc Peter Deisenroth
Publisher : Cambridge University Press
Page : 392 pages
File Size : 45,33 MB
Release : 2020-04-23
Category : Computers
ISBN : 1108569323
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Author : Daniel J. Velleman
Publisher : Cambridge University Press
Page : 401 pages
File Size : 21,53 MB
Release : 2006-01-16
Category : Mathematics
ISBN : 0521861241
Many students have trouble the first time they take a mathematics course in which proofs play a significant role. This new edition of Velleman's successful text will prepare students to make the transition from solving problems to proving theorems by teaching them the techniques needed to read and write proofs. The book begins with the basic concepts of logic and set theory, to familiarize students with the language of mathematics and how it is interpreted. These concepts are used as the basis for a step-by-step breakdown of the most important techniques used in constructing proofs. The author shows how complex proofs are built up from these smaller steps, using detailed 'scratch work' sections to expose the machinery of proofs about the natural numbers, relations, functions, and infinite sets. To give students the opportunity to construct their own proofs, this new edition contains over 200 new exercises, selected solutions, and an introduction to Proof Designer software. No background beyond standard high school mathematics is assumed. This book will be useful to anyone interested in logic and proofs: computer scientists, philosophers, linguists, and of course mathematicians.
Author : Paul R. Halmos
Publisher : American Mathematical Soc.
Page : 349 pages
File Size : 45,10 MB
Release : 1995-12-31
Category : Mathematics
ISBN : 1614442126
Linear Algebra Problem Book can be either the main course or the dessert for someone who needs linear algebraand today that means every user of mathematics. It can be used as the basis of either an official course or a program of private study. If used as a course, the book can stand by itself, or if so desired, it can be stirred in with a standard linear algebra course as the seasoning that provides the interest, the challenge, and the motivation that is needed by experienced scholars as much as by beginning students. The best way to learn is to do, and the purpose of this book is to get the reader to DO linear algebra. The approach is Socratic: first ask a question, then give a hint (if necessary), then, finally, for security and completeness, provide the detailed answer.
Author : Gilbert Strang
Publisher : Wellesley-Cambridge Press
Page : 0 pages
File Size : 39,41 MB
Release : 2016-08-11
Category : Mathematics
ISBN : 9780980232776
Linear algebra is something all mathematics undergraduates and many other students, in subjects ranging from engineering to economics, have to learn. The fifth edition of this hugely successful textbook retains all the qualities of earlier editions, while at the same time seeing numerous minor improvements and major additions. The latter include: • A new chapter on singular values and singular vectors, including ways to analyze a matrix of data • A revised chapter on computing in linear algebra, with professional-level algorithms and code that can be downloaded for a variety of languages • A new section on linear algebra and cryptography • A new chapter on linear algebra in probability and statistics. A dedicated and active website also offers solutions to exercises as well as new exercises from many different sources (including practice problems, exams, and development of textbook examples), plus codes in MATLAB®, Julia, and Python.
Author : Jonathan S. Golan
Publisher : Springer Science & Business Media
Page : 443 pages
File Size : 39,53 MB
Release : 2007-04-05
Category : Mathematics
ISBN : 1402054955
This book rigorously deals with the abstract theory and, at the same time, devotes considerable space to the numerical and computational aspects of linear algebra. It features a large number of thumbnail portraits of researchers who have contributed to the development of linear algebra as we know it today and also includes over 1,000 exercises, many of which are very challenging. The book can be used as a self-study guide; a textbook for a course in advanced linear algebra, either at the upper-class undergraduate level or at the first-year graduate level; or as a reference book.