BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Linear Algebra and Learning from Data

Linear Algebra and Learning from Data

Linear Algebra and Learning from Data
Stock photo: cover may vary

Linear Algebra and Learning from Data Hardback -

by NA

Add to wish list
  • New
New

Description

NA, NA. NEW.

Ask the seller a question Add to wish list
A$63.81
A$4.24 Delivery to USA
Standard delivery: 5 to 10 days
More delivery options
Ships from Schooltime Bookstore (Uttar Pradesh, India)

Details

  • Title Linear Algebra and Learning from Data
  • Author NA
  • Binding Hardback
  • Condition New
  • Pages 446
  • Volumes 1
  • Language ENG
  • Publisher NA
  • Publication date NA
  • Bookseller's Inventory # STCB0118
  • ISBN 9780692196380 / 0692196382
  • Category Mathematics
  • Quantity available 9

About Schooltime Bookstore Uttar Pradesh, India

Biblio member since 2024

We are bookseller based in Noida, India. We deal with educational books and fiction. We are into the business since last 20 years and always focus on customer satisfaction.

Terms of Sale:

30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from Schooltime Bookstore

Reader reviews for Linear Algebra and Learning from Data

From the publisher

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.
tracking-