About Us

Math shortcuts, Articles, worksheets, Exam tips, Question, Answers, FSc, BSc, MSc

More about us

Keep Connect with Us

  • =

Login to Your Account


JOIN OUR 150,890 + FANS
JOIN OUR 763 + FANS

40+ Linear Algebra Free Books


"Linear algebra" is generally classified into two main categories: "theoretical linear algebra" and "applied linear algebra". Both areas are deeply connected but serve different purposes. "Theoretical linear algebra" focuses on understanding abstract concepts like "vector spaces", "basis", "dimension", "eigenvalues", and "eigenvectors". It provides a framework for exploring how transformations work and why certain systems behave the way they do. This branch is essential for developing a deeper appreciation of mathematical theory and proofs. "Applied linear algebra", on the other hand, deals with practical computation and real-world applications. It includes solving matrix equations, performing "data analysis", and designing algorithms used in artificial intelligence, 3D modeling, and optimization. Engineers and scientists rely on applied linear algebra to solve real problems from controlling robots to predicting weather patterns.


For advanced learners, there are several "free Linear Algebra books", these books provide both theory and application with exercises for hands-on learning.

'
Free Linear Algebra Books
A Short Course in Theory of Determinants - Gifford Weld
This is a clear and concise book that explains "determinants", "algebra", and "linear algebra basics". It focuses on theory and understanding, making it useful for students learning the foundations of determinant theory.
Advanced Linear Algebra - David Surowski
This text explains linear algebra in a clear and logical way, focusing on "theory", "proofs", and "conceptual understanding". It helps students deeply understand vector spaces, transformations, and structure, making it ideal for advanced mathematics learners and future researchers.
Advanced Linear Algebra: Foundations to Frontiers Geijn
This text teaches "theory", "algorithms", and "computational" techniques in linear algebra. It combines rigorous mathematics with practical programming exercises, videos, and real-world examples, helping students and professionals understand both the concepts and their applications in scientific computing and data analysis.
Algorithms for Sparse Linear Systems by Jennifer Scott
This textbook explains efficient ways to solve large "sparse", "linear", and "computational" systems common in engineering and science. The book covers direct and iterative methods, factorization techniques, and preconditioners, helping readers understand and implement algorithms that take advantage of sparsity for faster, practical solutions.
An Elementary Treatise on Determinants by Lewis Carroll
This is a clear and beginner-friendly mathematics book that explains determinant concepts step by step. The author focuses on understanding rather than memorization, making it helpful for students building foundations in "determinants", "algebra", and "linear algebra".
Applied & Computational Linear Algebra - Charles Byrne
This book explains "linear algebra", "computational methods", and "algorithms" in a clear, practical way. The book shows how matrix techniques are used in real applications like optimization and data analysis, making it ideal for students who want both theory and real-world understanding.
Comprehensive Linear Algebra 1- Broida & Williamson PDF
This volume of the book explains "Linear Algebra" in a clear and easy way. It introduces "Matrices" and "Vector Spaces" with simple examples, helping beginners and students build a strong understanding of fundamental concepts step by step.
Comprehensive Linear Algebra 2- Broida & Williamson PDF
This volume 2 explains advanced "Linear Algebra" ideas using "Polynomials" and "Canonical Forms". It helps students understand eigenvalues and matrix structure in a clear, step-by-step way, building strong theoretical understanding.
Comprehensive Linear Algebra 3- Broida & Williamso
This third volume is most advanced volume of this serious of book, explains advanced "Linear Operators", "Tensors", and "Vector Spaces" in a clear and simple way. It helps students understand how linear transformations work in deeper mathematical structures.
Computational & Algorithmic Linear Algebra - Murty
"Computational and Algorithmic Linear Algebra and n-Dimensional Geometry" by Katta G. Murty explains linear algebra in a practical and easy way. It focuses on "computation", "algorithms", and "problem-solving", helping students understand how mathematical concepts are used in real applications across engineering, computer science, and applied mathematics.
Computational Methods of Linear Algebra - V. N Faddeeva
This text explains linear algebra from a practical viewpoint, focusing on "numerical methods", "matrix computation", and "accuracy". It teaches how to solve linear systems and eigenvalue problems, making it useful for engineers, scientists, and applied mathematics learners.
Contributions To History Of Determinants - Thomas Muir
This is a detailed historical book that records how determinant theory developed in the early twentieth century. It focuses on research progress and key contributors, making it valuable for readers interested in "determinants", "mathematical history", and "classical algebra".
Determinants by Gifford Laenas Weld - PDF
This is a clear and structured mathematics book that explains the core ideas of determinants. It focuses on definitions, properties, and calculation methods, helping students build a strong foundation for "linear algebra", "matrix theory", and "advanced algebra" through logical and easy-to-follow explanations.
Exercises and Problems in Linear Algebra by John Erdman
This textbook focuses on "practice", "concepts", and "problem-solving". The book offers a wide range of exercises on vector spaces, linear transformations, eigenvalues, and diagonalization, with answers for self-study. It helps students strengthen understanding and build confidence through hands-on, structured practice.
Foundations of Signal Processing - Martin Vetterli
This text explains "signal processing", "Fourier transforms", and "sampling" in a clear, practical way. It covers how signals behave, how they are analyzed, and how compression works, making it ideal for students and professionals seeking a solid understanding of modern signal processing.
From Determinant To Tensor by William Sheppard - PDF
This book explains how mathematics moves from "determinants" to "tensors" through "linear algebra". The book focuses on ideas and theory, showing how modern algebra developed from classical methods in a clear and logical way.
An Introduction to Determinants by William Thomson -PDF
This text explains "determinants", "matrices", and "linear systems". It teaches how to compute determinants, explore their properties, and apply them to solve linear equations. Students learn how determinants indicate matrix invertibility, aid in Cramer’s Rule, and connect to eigenvalues, volumes, and transformations in linear algebra.
Iterative Methods for Sparse Linear Systems Yousef Saad
This book explains how to solve large sparse linear systems efficiently. It focuses on "iterative methods", "sparse matrices", and "scientific computing", making it an essential reference for graduate students and researchers in applied mathematics and engineering.
Lecture Notes of Matrix Computations by Wen Wei Lin
This is a graduate-level book that explains how matrix algorithms work in real computations. It focuses on "numerical linear algebra", "matrix algorithms", and "computational accuracy", helping students understand both theory and practical problem-solving in scientific computing.
Linear Algebra by André Hensbergen, Nikolaas Verhulst
This textbook explains the basics of vectors, matrices, and equations in a clear way. The book builds understanding step by step and uses practical examples to connect theory. It suits students in science, engineering, and computing with "clear concepts", "useful examples", "strong foundations" learning.
Linear Algebra by Wikibooks - FreeMathematicsBooks.com
"Linear Algebra" by Wikibooks" is a free, open-source textbook that introduces core linear algebra concepts in a clear and simple way. It covers vectors, matrices, linear equations, and transformations, making it suitable for beginners, students, and self-learners.
Linear Algebra for Computer Vision & ML - Jean Gallier
This text explains core math ideas in a clear, practical way. It builds strong foundations in vectors, matrices, and transformations, showing how they power "computer vision", "robotics", and "machine learning" through real applications and intuitive explanations for students researchers engineers alike worldwide today.
Linear Algebra via Exterior Products by Sergei Winitzki
This textbook teaches "linear algebra", "exterior products", and "vector spaces". It uses a coordinate-free approach to explore determinants, eigenvalues, and the Jordan form, helping students understand the underlying structures of linear algebra. The book blends geometric intuition with algebraic rigor for deeper comprehension.
Linear Algebra: Foundations to Frontiers - M.E. Myers
This text explains linear algebra in a clear, practical way. It connects "theory", "computation", and "applications", showing how vectors and matrices become real algorithms. The book emphasizes problem solving and numerical thinking, helping students understand concepts deeply while learning how linear algebra powers engineering and data science.
Linear Algebra: Introduction to Abstract Math - Lankham
This text teaches "abstract", "proof-based", and "computational" aspects of linear algebra. It covers vector spaces, linear maps, eigenvalues, and determinants, helping students build strong reasoning skills while connecting practical calculations to deeper mathematical theory through exercises and clear explanations.
Linear Algebra Lecture Notes by Greg Mayer - PDF
This book offer a clear and easy introduction to "Linear Algebra". The notes explain "Matrices" and "Vectors" with simple examples and step-by-step methods, making them ideal for beginners, students, and self-learners building a strong foundation.
Linear Algebra, Theory And Applications Kenneth Kuttler
This text teaches "theory", "applications", and "computational" methods in linear algebra. It covers matrices, vector spaces, linear transformations, determinants, and eigenvalues, blending rigorous explanations with practical examples, helping students understand both the mathematical foundations and how to apply them in real-world problem-solving.
Linear Transformations on Vector Spaces- Scott Kaschner
This text is a concept-focused introduction to "Linear Algebra". It helps students understand "Vector Spaces" and "Linear Transformations" through clear explanations and logical structure, making abstract ideas easier to grasp for undergraduate learners.
Matrices and Determinoids 1 by Cuthbert Cullis - PDF
This volume of textbook introduces "rectangular matrices", "determinoids", and their algebraic properties. This book lays the foundation of a three-volume series, explaining matrix structure, rank, and linear equations in a clear, classical, and theory-focused style.
Matrices and Determinoids 2 by Cuthbert Cullis - PDF
This volume expands the theory of "matrices", "determinoids", and "linear algebra". It builds on Volume I by explaining advanced properties and structures in a clear, classical, and proof-focused style for serious mathematics readers.
Matrices and Determinoids 3 by Cuthbert Cullis - PDF
This is a classic mathematics book that explains advanced ideas in "matrix theory", "determinoids", and "linear algebra". It focuses on theory and proofs, making it useful for readers interested in the historical foundations of matrix mathematics.
Matrix Algebra by Marco Taboga
This is an easy-to-understand book that explains matrix concepts for students in statistics and economics. It focuses on "matrix algebra", "statistical applications", and "linear systems", using clear examples and solved exercises to support learning.
Matrix Theory and Linear Algebra by Peter Selinger
This text explains "Linear Algebra" through "Matrices" in a clear and logical way. It covers vectors, transformations, and eigenvalues with simple explanations, making it ideal for students and self-learners building a strong mathematical foundation.
n-Linear Algebra of Type II by W. B. Vasantha Kandasamy
This text teaches "n-linear algebra", "vector spaces", and "eigenvalues". It generalizes traditional linear algebra to handle complex data, introducing n-vector spaces, n-inner products, and n-linear functionals. The book includes problems and applications in coding theory and characteristic polynomials.
Notes for Computational Linear Algebra by Jessy Grizzle
This text explains linear algebra in a practical way, focusing on "computation", "applications", and "problem-solving". It helps students use matrices and linear systems in robotics and engineering, making math useful, clear, and easy to apply in real projects.
Numerical Linear Algebra by Pavel Cížek, Lenka Cížková
This textbook explains how "numerical methods", "matrix computations", and "linear systems" are used to solve real-world problems. The book focuses on practical algorithms behind data analysis, optimization, and scientific computing, helping readers connect theory with efficient computational practice.
Numerical Methods for Large Eigenvalue Problems -Saad
This book explains how to compute eigenvalues for very large matrices using efficient numerical techniques. It focuses on "large eigenvalue problems", "Krylov subspace methods", and "sparse matrices", making it a key reference for graduate students and researchers in scientific and engineering computing.
Set Linear Algebra and Set Fuzzy Linear Algebra - PDF
This text introduces "set vector spaces", "set linear algebra", and "fuzzy analogues". The book generalizes traditional vector spaces, making them accessible to non-mathematicians. It explores advanced structures like biset bivector spaces, fuzzy n-set vector spaces, and provides over 300 problems for practice.
Some Linear Algebra for Econometrics by Frank Pinter
This text is a short and practical guide that explains "linear algebra", "matrices", and "projections" used in econometrics. It helps economics students understand regression and econometric theory with clear explanations, focusing on useful concepts rather than heavy mathematical proofs.
Special Set Linear Algebra and Special Set Fuzzy Linear
This textbook teaches "set theory", "linear algebra", and "fuzzy systems". It extends traditional vector spaces to finite sets and incorporates fuzziness, helping students and professionals model uncertain or imprecise data in computing, cryptography, and multi-expert systems.
Super Linear Algebra by W. B. Vasantha Kandasamy PDF
This text introduces a modern extension of linear algebra using "super vector spaces" and "super matrices". Written by Vasantha Kandasamy & Florentin Smarandache, the book explains how classical ideas like dimension and transformations expand into "generalized algebra", helping advanced learners model complex, multi-structured systems effectively and clearly.
Super Special Codes Using Super Matrices - V. Kandasamy
This text explores new ideas in "Coding Theory" using advanced "Super Matrices". The book explains how these structures help build novel coding systems, making it useful for readers interested in "Information Theory" and advanced mathematics.
Tea Time Linear Algebra by Leon Q. Brin - PDF
This text is a friendly introduction to "Linear Algebra". It explains ideas like matrices and vector spaces using clear language and examples, helping students build "Conceptual Understanding" and confidence in "Mathematics" without feeling overwhelmed.
Templates for the Solution of Linear Systems by Barrett
This book is a practical guide for solving large systems of equations using efficient numerical methods. It explains how to choose and apply "iterative methods", handle "sparse matrices", and use "preconditioning" to improve performance in scientific and engineering computing.
The Theory of Determinants and Their Applications - PDF
This text explains "determinants", "geometry", and "applications". The book explores determinant properties, historical developments, and methods for solving mathematical and geometric problems. It shows how determinants help analyze matrix behavior, understand geometric structures, and apply linear algebra concepts in practical and theoretical contexts.
Theory of Determinants for Colleges by Paul Hanus - PDF
This is a clear and well-structured mathematics book written for college students. It explains determinant concepts step by step, focusing on understanding and logical proofs, and helps learners build foundations in "determinants", "algebra", and "linear algebra".
Theory of Determinants for Colleges & Schools - T. Muir
This is a clear and well-organized mathematics book that explains determinant theory step by step. It combines theory with practice through graded exercises, helping learners build strong skills in "determinants", "algebra", and "linear algebra" foundations.
Theory of Determinants Historical Order Thomas Muir
This textbook explains how determinant theory evolved over time. The book follows key discoveries and mathematicians in chronological order, showing the growth of ideas and methods. It is valuable for readers interested in "determinants", "mathematical history", and "classical algebra".
Theory Of Determinants Matrices & Invariants - Turnbull
This is a classic book that explains "determinants", "matrices", and "invariant theory" in a clear and logical way. It focuses on mathematical theory and proofs, making it useful for readers interested in the foundations of linear algebra.
Related Books Categories
Linear Algebra (Introduction)

.