Linear Algebra and Learning from Data

by Gilbert Strang

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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 marices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

Format:Hardcover

Language:English

ISBN:0692196382

ISBN13:9780692196380

Release Date:January 2019

Publisher:Wellesley College

Length:446 Pages

Weight:2.10 lbs.

Related Subjects

Computers Computers & Technology Math Mathematics Science & Math

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Linear Algebra and Learning from Data

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