Linear Algebra Elizabeth S. Meckes, Mark W. Meckes

Published in honor of his 70th birthday, this volume explores and celebrates the work of G.W. (Pete) Stewart, a world-renowned expert in computational linear algebra. It is widely accepted that Stewart is the successor to James Wilkinson, the first giant in the field, taking up the perturbation theory research that Wilkinson so ably began and using it as a foundation for algorithmic insights.

Learn everything from Linear Algebra, then test your knowledge with 400+ practice questions

Interested in increasing your Machine Learning, Deep Learning expertise by effectively applying the mathematical skills? Then, this course is for you. With the growing learners of Machine Learning, Data Science, and Deep Learning.

Linear algebra is the branch of mathematics that has grown from a care­ ful study of the problem of solving systems of linear equations. The ideas that developed in this way have become part of the language of much of higher mathematics.

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This unique text provides a geometric approach to group theory and linear algebra, bringing to light the interesting ways in which these subjects interact. Requiring few prerequisites beyond understanding the notion of a proof, the text aims to give students a strong foundation in both geometry and algebra. Starting with preliminaries (relations, elementary combinatorics, and induction), the book then proceeds to the core topics: the elements of the theory of groups and fields (Lagrange's Theorem, cosets, the complex numbers and the prime fields), matrix theory and matrix groups, determinants, vector spaces, linear mappings, eigentheory and diagonalization, Jordan decomposition and normal form, normal matrices, and quadratic forms. The final two chapters consist of a more intensive look at group theory, emphasizing orbit stabilizer methods, and an introduction to linear algebraic groups, which enriches the notion of a matrix group.