000 | 01473nam a22001937a 4500 | ||
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005 | 20241114205431.0 | ||
008 | 241114b |||||||| |||| 00| 0 eng d | ||
020 | _a9781944660345 | ||
082 |
_a512.5 _bJEA |
||
100 |
_aJean Gallier _918299 |
||
245 |
_aLinear algebra and optimization with applications to machine learning: _blinear algebra for computer vision, robotics, and machine learning |
||
260 |
_bWorld Scientific Publishing _aSingapore _c2023 |
||
300 | _axv, 806 p. | ||
365 |
_aINR _b2995.00 |
||
520 | _aThis 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. (https://www.worldscientific.com/worldscibooks/10.1142/11446#t=aboutBook) | ||
650 | _aAlgebras, Linear | ||
700 |
_aQuaintance, Jocelyn _918663 |
||
942 |
_cBK _2ddc |
||
999 |
_c7764 _d7764 |