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> Introduction to Applied Linear Algebra

Introduction to Applied Linear Algebra Vectors, Matrices, and Least Squares

Authors

Stephen Boyd, Stanford University, California, Lieven Vandenberghe, University of California, Los Angeles
Published 2018

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…

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Key features

  • Shows students how a few fundamental linear algebra concepts and techniques underlie a wide variety of applications
  • Provides a revolutionary new approach to teaching linear algebra methods to aspiring data scientists
  • Includes numerous practical examples and exercises, allowing students to translate their knowledge of abstract linear algebra into real-world applications

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