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- Title: Linear Algebra with Applications
- Author(s) W. Keith Nicholson
- Publisher: McGraw Hill, 6th ed (2009); eBook (Open Edition, 2019, Creative Commons Licensed)
- License(s): Creative Commons License (CC)
- Hardcover: 544 pages
- eBook: PDF (698 pages)
- Language: English
- ISBN-10: 0070985103
- ISBN-13: 978-0070985100
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The aim of the text is to achieve a balance among computational skills, theory, and applications of linear algebra. It is a relatively advanced introduction to the ideas and techniques of linear algebra targeted for science and engineering students who need to understand not only how to use these methods but also gain insight into why they work.
It introduces the general idea of Linear Algebra much earlier than the competition keeping with the same rigorous and concise approach to linear algebra. Along with the many diagrams and examples that help students visualize, it also keeps with the continuous introduction of concepts.
About the Authors- N/A
- Linear Algebra and Matrix Algebra
- Algebra, Abstract Algebra, and Linear Algebra
- Computational and Algorithmic Mathematics
- Calculus and Mathematical Analysis
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Linear Algebra: Theory, Intuition, Code (Mike X Cohen)
Are you ready to dive into the vibrant world of linear algebra and see how it powers real-world applications? Welcome to this comprehensive guide, where traditional theory meets modern computational practices.
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Linear Algebra: Theory, Intuition, Code (Mike X Cohen)
Are you ready to dive into the vibrant world of linear algebra and see how it powers real-world applications? Welcome to this comprehensive guide, where traditional theory meets modern computational practices.
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Exercises and Problems in Linear Algebra (John M Erdman)
This book contains an extensive collection of exercises and problems that address relevant topics in linear algebra. The exercises will be both interesting and helpful to an average student.
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Linear Algebra with Python (Sean Fitzpatrick)
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Understanding Linear Algebra (David Austin)
The text aims to support readers as they develop their ability to think about linear algebra conceptually, their computational fluency (with SageMath), and their understanding of the role that linear algebra plays in shaping our society.
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Advanced Linear Algebra (David Surowski)
This book explores a variety of advanced topics in linear algebra that highlight the rich interconnections of the subject to geometry, algebra, analysis, combinatorics, numerical computation, and many other areas of mathematics.
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This textbook covers linear systems and Gauss' method, vector spaces, linear maps and matrices, determinants, and eigenvectors and eigenvalues. Each chapter has three or four discussions of additional topics and applications.
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A First Course in Linear Algebra (Ken Kuttler)
The book presents an introduction to the fascinating subject of linear algebra. As the title suggests, this text is designed as a first course in linear algebra for students who have a reasonable understanding of basic algebra.
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Fundamentals of Matrix Algebra (Gregory Hartman)
A college (or advanced high school) level text dealing with the basic principles of matrix and linear algebra. It covers solving systems of linear equations, matrix arithmetic, the determinant, eigenvalues, and linear transformations.
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Matrix Algebra (Marco Taboga)
This is a course in matrix algebra, with a focus on concepts that are often used in probability and statistics. Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory.
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Matrix Algebra with Computational Applications (Dirk Colbry)
This book is designed to introduce students to the use of Linear Algebra to solve real-world problems. These materials were developed specifically for students and instructors that emphasizes hands-on problem-solving activities.
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