Linear algebra has become the subject to know for people in quantitative disciplines of all kinds. No longer the exclusive domain of mathematicians and engineers, it is now used everywhere there is data and everybody who works with data needs to know more. This new book from Professor Gilbert Strang, author of the acclaimed Introduction to Linear Algebra, now in its fifth edition, makes linear algebra accessible to everybody, not just those with a strong background in mathematics. It takes a mo…
Linear algebra has become the subject to know for people in quantitative disciplines of all kinds. No longer the exclusive domain of mathematicians and engineers, it is now used everywhere there is data and everybody who works with data needs to know more. This new book from Professor Gilbert Strang, author of the acclaimed Introduction to Linear Algebra, now in its fifth edition, makes linear algebra accessible to everybody, not just those with a strong background in mathematics. It takes a more active start, beginning by finding independent columns of small matrices, leading to the key concepts of linear combinations and rank and column space. From there it passes on to the classical topics of solving linear equations, orthogonality, linear transformations and subspaces, all clearly explained with many examples and exercises. The last major topics are eigenvalues and the important singular value decomposition, illustrated with applications to differential equations and image compression. A final optional chapter explores the ideas behind deep learning.
Linear algebra has become the subject to know for people in quantitative disciplines of all kinds. No longer the exclusive domain of mathematicians and engineers, it is now used everywhere there is data and everybody who works with data needs to know more. This new book from Professor Gilbert Strang, author of the acclaimed Introduction to Linear Algebra, now in its fifth edition, makes linear algebra accessible to everybody, not just those with a strong background in mathematics. It takes a more active start, beginning by finding independent columns of small matrices, leading to the key concepts of linear combinations and rank and column space. From there it passes on to the classical topics of solving linear equations, orthogonality, linear transformations and subspaces, all clearly explained with many examples and exercises. The last major topics are eigenvalues and the important singular value decomposition, illustrated with applications to differential equations and image compression. A final optional chapter explores the ideas behind deep learning.
Atsiliepimai
Atsiliepimų nėra
0 pirkėjai įvertino šią prekę.
5
0%
4
0%
3
0%
2
0%
1
0%
Kainos garantija
Ženkliuku „Kainos garantija” pažymėtoms prekėms Knygos.lt garantuoja geriausią kainą. Jei identiška prekė kitoje internetinėje parduotuvėje kainuoja mažiau - kompensuojame kainų skirtumą. Kainos lyginamos su knygos.lt nurodytų parduotuvių sąrašu prekių kainomis. Knygos.lt įsipareigoja kompensuoti kainų skirtumą pirkėjui, kuris kreipėsi „Kainos garantijos” taisyklėse nurodytomis sąlygomis. Sužinoti daugiau
Elektroninė knyga
22,39 €
DĖMESIO!
Ši knyga pateikiama ACSM formatu. Jis nėra tinkamas įprastoms skaityklėms, kurios palaiko EPUB ar MOBI formato el. knygas.
Svarbu! Nėra galimybės siųstis el. knygų jungiantis iš Jungtinės Karalystės.
Tai knyga, kurią parduoda privatus žmogus. Kai apmokėsite užsakymą, jį per 7 d. išsiųs knygos pardavėjas . Jei to pardavėjas nepadarys laiku, pinigai jums bus grąžinti automatiškai.
Šios knygos būklė nėra įvertinta knygos.lt ekspertų, todėl visa atsakomybė už nurodytą knygos kokybę priklauso pardavėjui.
Atsiliepimai