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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
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  • Title Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
  • Author(s) Stephen Boyd, Lieven Vandenberghe
  • Publisher: Cambridge University Press; 1 edition (August 23, 2018)
  • License(s): "Copyright in this book is held by Cambridge University Press, who have kindly agreed to allow us to keep the book available on the web"
  • Hardcover 474 pages
  • eBook PDF (698 pages)
  • Language: English
  • ISBN-10: 1316518965
  • ISBN-13: 978-1316518960
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Book Description

This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra. Requiring no prior knowledge of the subject, it covers the aspects of linear algebra - vectors, matrices, and least squares - that are needed for engineering applications, discussing examples across data science, machine learning and artificial intelligence, signal and image processing, tomography, navigation, control, and finance.

The numerous practical exercises throughout allow students to test their understanding and translate their knowledge into solving real-world problems, with lecture slides, additional computational exercises in Julia and MATLAB, and data sets accompanying the book online. It is suitable for both one-semester and one-quarter courses, as well as self-study, this self-contained text provides beginning students with the foundation they need to progress to more advanced study.

About the Authors
  • Stephen Boyd is the Samsung Professor of Engineering, and Professor of Electrical Engineering at Stanford University,California, with courtesy appointments in the Department of Computer Science, and the Department of Management Science and Engineering. He is the co-author of Convex Optimization (Cambridge, 2004), written with Lieven Vandenberghe.
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