Linear Algebra and Learning from Data

Linear Algebra and Learning from Data by Gilbert Strang

Linear algebra and the foundations of deep learning, together at last From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

Gilbert Strang is a well-known MIT mathematician who works in the fields of scientific research and other areas of applied mathematics.

SKU	Nicht verfügbar
ISBN 13	9780692196380
ISBN 10	0692196382
Titel	Linear Algebra and Learning from Data
Autor	Gilbert Strang
Buchzustand	Nicht verfügbar
Bindungsart	Hardback
Verlag	Wellesley-Cambridge Press,U.S.
Erscheinungsjahr	2019-01-31
Seitenanzahl	446
Hinweis auf dem Einband	Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden.
Hinweis	Nicht verfügbar