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Synopsis
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. 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.
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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.
Lieven Vandenberghe is a Professor in the Electrical and Computer Engineering Department at the University of California, Los Angeles, with a joint appointment in the Department of Mathematics. He is the co-author, with Stephen Boyd, of Convex Optimization (Cambridge, 2004).
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Introduction to Applied Linear Algebra : Vectors, Matrices, and Least Squares
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Cambridge University Press, 2018
ISBN 10: 1316518965
ISBN 13: 9781316518960
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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
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ISBN 10: 1316518965
ISBN 13: 9781316518960
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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
Published by
Cambridge University Press (edition 1), 2018
ISBN 10: 1316518965
ISBN 13: 9781316518960
Used
Hardcover
Seller: BooksRun, Philadelphia, PA, U.S.A.
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Hardcover. Condition: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Seller Inventory # 1316518965-8-1
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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
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ISBN 10: 1316518965
ISBN 13: 9781316518960
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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
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ISBN 10: 1316518965
ISBN 13: 9781316518960
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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
Published by
Cambridge University Press, 2018
ISBN 10: 1316518965
ISBN 13: 9781316518960
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Introduction to Applied Linear Algebra : Vectors, Matrices, and Least Squares
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ISBN 10: 1316518965
ISBN 13: 9781316518960
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Introduction to Applied Linear Algebra : Vectors, Matrices, and Least Squares
Published by
Cambridge University Press, 2018
ISBN 10: 1316518965
ISBN 13: 9781316518960
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Introduction to Applied Linear Algebra (Hardcover)
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ISBN 10: 1316518965
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Hardcover. Condition: new. Hardcover. 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. 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. A groundbreaking introductory textbook covering the linear algebra methods needed for data science and engineering applications. It combines straightforward explanations with numerous practical examples and exercises from data science, machine learning and artificial intelligence, signal and image processing, navigation, control, and finance. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781316518960
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Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares
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ISBN 10: 1316518965
ISBN 13: 9781316518960
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