Normal view MARC view ISBD view

Linear algebra for data science, machine learning, and signal processing

By: Fessler, Jeffrey A.
Contributor(s): Nadakuditi, Raj Rao.
Publisher: London : Cambridge University Press, 2024Description: xviii, 431 p. ; ill., (Chifly col.), 25 cm.ISBN: 9781009418140.Subject(s): Algebras, Linear | Machine learning | Mathematics | Matrices | Signal processingDDC classification: 512.5 Summary: Master basic matrix methods by seeing how the math is used in practice in a range of data-driven applications. Includes a wealth of engaging exercises for quizzes, self-study and interactive learning, as well as online JULIA demos offering a hands-on learning experience for upper-level undergraduates and first-year graduate students.
Tags from this library: No tags from this library for this title. Log in to add tags.

Includes bibliographical references and index.

Master basic matrix methods by seeing how the math is used in practice in a range of data-driven applications. Includes a wealth of engaging exercises for quizzes, self-study and interactive learning, as well as online JULIA demos offering a hands-on learning experience for upper-level undergraduates and first-year graduate students.

There are no comments for this item.

Log in to your account to post a comment.

Powered by Koha