Trending Bestseller

Numerical Linear Algebra with Julia

No reviews yet Write a Review
Paperback / softback
277 Pages
30 November 2021
$206.00
Ships in 2-5 business days

Delivery estimate

Hurry up! Current stock:
Numerical Linear Algebra with Julia provides in-depth coverage of fundamental topics in numerical linear algebra, including how to solve dense and sparse linear systems, compute QR factorizations, compute the eigendecomposition of a matrix, and solve linear systems using iterative methods such as conjugate gradient. The style is friendly and approachable and cartoon characters guide the way. Inside this book, readers will find detailed descriptions of algorithms, implementations in Julia that illustrate concepts and allow readers to explore methods on their own, and illustrations and graphics that emphasize core concepts and demonstrate algorithms. Numerical Linear Algebra with Julia is a textbook for undergraduate and graduate students. It is appropriate for the following courses: Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. The book may also serve as a reference for researchers in various fields such as computational engineering, statistics, data-science, and machine learning, who depend on numerical solvers in linear algebra.

You Can Find This Title In

    Product Details
    ISBN-13
    9781611976540
    Author
    Eric Darve
    Publisher
    SIAM - SOCIETY FOR INDUSTRIAL AND APPLIED
    Published
    30 November 2021
    Format
    Paperback / softback
    Pages
    277

    This product hasn't received any reviews yet. Be the first to review this product!

    $206.00
    Ships in 2-5 business days

    Delivery estimate

    Hurry up! Current stock:

    Numerical Linear Algebra with Julia

    $206.00

    Description

    Numerical Linear Algebra with Julia provides in-depth coverage of fundamental topics in numerical linear algebra, including how to solve dense and sparse linear systems, compute QR factorizations, compute the eigendecomposition of a matrix, and solve linear systems using iterative methods such as conjugate gradient. The style is friendly and approachable and cartoon characters guide the way. Inside this book, readers will find detailed descriptions of algorithms, implementations in Julia that illustrate concepts and allow readers to explore methods on their own, and illustrations and graphics that emphasize core concepts and demonstrate algorithms. Numerical Linear Algebra with Julia is a textbook for undergraduate and graduate students. It is appropriate for the following courses: Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. The book may also serve as a reference for researchers in various fields such as computational engineering, statistics, data-science, and machine learning, who depend on numerical solvers in linear algebra.

    You Can Find This Title In

      This Title Is Categorised As