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  • Linr Algebra & Optim Appl (V1) by Gallier Jean book cover
  • Linr Algebra & Optim Appl (V1) by Gallier Jean book cover
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Linr Algebra & Optim Appl (V1)

by Gallier Jean

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Linear algebra foundations for applied research

$103.08 USD
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Paperback New English

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Linear algebra foundations for applied research

Starting from calculus, this volume develops linear algebra for work in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. Its coverage moves from vector spaces, bases, and linear maps to duality, Hermitian spaces, spectral theorems, singular value decomposition, and the primary decomposition theorem. The combination of mathematical explanations and applications makes it a substantial reference for understanding the theory behind tools used across these fields. At 824 pages, it offers room for both foundational concepts and more advanced topics.

Good fit for readers who enjoy

  • Computer scientists and engineers seeking the mathematics behind applied tools
  • Mathematicians working across applied fields
  • Learners with a calculus background studying linear algebra

Themes

Linear algebra foundationsSpectral theory and SVDApplications in computing and engineering

Based on publisher information and book metadata.

Book overview

This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields.

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