Description

Book Synopsis
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.

Linear Algebra And Optimization With Applications

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    £81.00

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    RRP £90.00 – you save £9.00 (10%)

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    A Paperback / softback by Jean H Gallier, Jocelyn Quaintance

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      Publisher: World Scientific Publishing Co Pte Ltd
      Publication Date: 07/02/2020
      ISBN13: 9789811207716, 978-9811207716
      ISBN10: 9811207712
      Also in:
      Computing Computer vision Machine learning Maths for computer scientists

      Description

      Book Synopsis
      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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