Numerical Linear Algebra Julia by Eric Darve (14 results)

Condition: New. 2021. Hardcover. . . . . .

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condition: new. Paperback. 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 finddetailed descriptions of algorithms,implementations in Julia that illustrate concepts and allow readers to explore methods on their own, andillustrations 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback / Softback. Condition: Brand New. 277 pages. 10.08x6.97x1.06 inches. In Stock.

Condition: New.

Condition: New.

Condition: New. 2021. Hardcover. . . . . . Books ship from the US and Ireland.

Paperback. Condition: New. 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 finddetailed descriptions of algorithms,implementations in Julia that illustrate concepts and allow readers to explore methods on their own, andillustrations 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.

Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 874.

Condition: New. In.

Paperback. Condition: new. Paperback. 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 finddetailed descriptions of algorithms,implementations in Julia that illustrate concepts and allow readers to explore methods on their own, andillustrations 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Einband - flex.(Paperback). Condition: New. 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 suc.

Paperback. Condition: New. 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 finddetailed descriptions of algorithms,implementations in Julia that illustrate concepts and allow readers to explore methods on their own, andillustrations 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.

Philadelphia, Society for Industrial and Applied Mathematics, [2021]. XIII,406 pp. Ills (chiefly col.). Softcover. 8vo. [ISBN: 9781611976540]. - As new."This book is an engaging and accessible adventure through numerical linear algebra-including homework assignments-aimed at graduate students and advanced undergraduate students with interest in numerical methods and scientific computing" (Provided by publisher).