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Linear algebra and learning from data

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Artikelnr: SK0216814-SE20260527-055838 Kategori: Etikett:

Beskrivning

Beskrivning

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.

Om boken

Om denna bok

Linear algebra and learning from data av Gilbert (massachusetts Institute Of Technology) Strang är en Danskt band bok med 431 sidor på Engelska. Den utgavs 2019 av Cambridge University Press.

Produktinformation

Kategori
Data & IT
Bandtyp
Danskt band
Språk
Engelska
ISBN
9780692196380
Upplaga
0
Utgiven
2019-01-31
Förlag
Cambridge University Press
Sidantal
431