Linear Algebra and Optimization with Applications to Machine Learning - Volume I: Linear Algebra for Computer Vision, Robotics, and Machine Learning


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Description

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.

Author: Jean H. Gallier, Jocelyn Quaintance
Publisher: World Scientific Publishing Company
Published: 02/07/2020
Pages: 824
Binding Type: Hardcover
Weight: 2.78lbs
Size: 9.00h x 6.00w x 1.69d
ISBN13: 9789811206399
ISBN10: 9811206392
BISAC Categories:
- Mathematics | Algebra | Linear
- Mathematics | Optimization
- Computers | Computer Science