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Linear Algebra and Learning from Data
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Linear Algebra and Learning from Data

Book Details

Format Hardback or Cased Book
ISBN-10 0692196382
ISBN-13 9780692196380
Publisher Wellesley-Cambridge Press,U.S.
Imprint Wellesley-Cambridge Press,U.S.
Country of Manufacture US
Country of Publication GB
Publication Date Jan 31st, 2019
Print length 446 Pages
Weight 924 grams
Dimensions 23.90 x 20.40 x 1.90 cms
Product Classification: Mathematical modelling
Ksh 11,800.00
Publisher Out of Stock

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From Gilbert Strang, the first textbook that teaches linear algebra together with deep learning and neural nets.
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.

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