Introduction to Applied Linear Algebra: Vectors, Matrices and Least Squares by Stephen Boyd, Lieven Vandenberghe
Book Contents :-
1. Vectors
2. Linear functions
3. Norm and distance
4. Clustering
5. Linear independence
6. Matrices
7. Matrix examples
8. Linear equations
9. Linear dynamical systems
10. Matrix multiplication
11. Matrix inverses
12. Least squares
13. Least squares data fitting
14. Least squares classification
15. Multi-objective least squares
16. Constrained least squares
17. Constrained least squares applications
18. Nonlinear least squares
19. Constrained nonlinear least squares
About this book :-
"Introduction to Applied Linear Algebra: Vectors, Matrices and Least Squares" by Stephen Boyd and Lieven Vandenberghe is a clear, application-oriented book that teaches linear algebra through real-world problems. Instead of heavy abstraction, it focuses on how "vectors" and "matrices" are used in engineering, data science, and computational fields. The authors emphasize intuition, geometry, and practical meaning behind each concept, making the subject approachable and useful.
A central theme of the book is "least squares", which serves as a unifying idea across many applications such as data fitting, estimation, and approximation. Core topics like linear independence, eigenvalues, norms, and matrix factorizations are introduced with strong motivation and concrete examples. The book shows how linear algebra underpins modern areas like "optimization" and "machine learning", helping readers connect theory to practice.
Designed for students and professionals in applied mathematics, engineering, and computer science, the book balances clarity with depth. Its step-by-step explanations, real applications, and computational focus make it an excellent resource for building a solid foundation in "applied linear algebra" while developing practical problem-solving skills.
Book Detail :-
Title:
Introduction to Applied Linear Algebra: Vectors, Matrices and Least Squares by Stephen Boyd, Lieven Vandenberghe
Publisher:
Cambridge University Press
Year:
2018
Pages:
473
Type:
PDF
Language:
English
ISBN-10 #:
1316518965
ISBN-13 #:
978-1316518960
License:
External Educational Resource
Amazon:
Amazon
About Author :-
The author
Stephen Boyd
is a Professor of Engineering, and Professor of Electrical Engineering at Stanford University and a leading figure in "optimization", "convex analysis", and "control systems". He is widely known for transforming complex mathematical theory into practical tools used in engineering, data science, and large-scale computation. "Lieven Vandenberghe" is a professor at UCLA with expertise in "applied linear algebra" and "signal processing". Together, Boyd and Vandenberghe are recognized for their clear teaching style, strong focus on "matrices" and "least squares", and their lasting impact on modern applied mathematics education.
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