Matrix Theory and Linear Algebra by Peter Selinger

About this book :-
"Matrix Theory and Linear Algebra" by "Peter Selinger" is a clear and well-written textbook designed for undergraduate students and self-learners. The book focuses on understanding linear algebra through matrices, making abstract ideas easier to follow. Its structured approach helps readers build concepts step by step with strong mathematical clarity. The content covers essential topics such as "matrices", "vector spaces", "linear transformations", "determinants", and "eigenvalues". Each topic is explained with precise definitions, logical proofs, and worked examples. One of the key strengths of this book is that it is freely available and suitable for independent study. It is often used as lecture notes or a main reference in university courses, especially in mathematics and computer science. Overall, "Matrix Theory and Linear Algebra" is a reliable and rigorous resource for anyone seeking a strong foundation in modern "linear algebra".

Book Detail :-
Title: Matrix Theory and Linear Algebra by Peter Selinger
Publisher: Open Educational Text
Year: 1905
Pages: 561
Type: PDF
Language: English
ISBN-10 #: N\A
ISBN-13 #: N\A
License: CC BY 4.0
Amazon: Amazon

About Author :-
The author Peter Selinger is a mathematician and computer scientist known for his clear teaching style in "Linear Algebra". He is a professor at Dalhousie University and has extensive experience explaining complex topics such as "Matrix Theory" in a structured and student-friendly way. His academic work connects "Linear Transformations" with theoretical computer science and modern mathematics. Through his freely available lecture notes, Selinger supports "Mathematics Education" by making high-quality learning resources accessible to students worldwide.

Book Contents :-
1. Systems of Linear Equations 2. Vectors in Rn 3. Lines and Planes in Rn 4. Matrices 5. Spans, Linear Independence, and Bases in Rn 6. Linear Transformations in Rn 7. Determinants 8. Eigenvalues, Eigenvectors, and Diagonalization 9. Vector Spaces 10. Linear Transformation of Vector Spaces 11. Inner Product Spaces 12. Appendix A: Complex Numbers

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