Nonfiction | Computer & Technology

Linear Algebra and Optimization with Applications to Machine Learning

by Jean H Gallier

2020-05-29 11:02:31

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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 rigo... Read more
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. Less

Book Details

File size0 X 0 X 0 in
Print pages824
PublisherWorld Scientific Publishing
Publication date January 22, 2020
Languageeng
ISBN9789811206412
autor-image
Jean H. Gallier
Author
...

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