Numerical Linear Algebra: Theorems, Proofs, and Python Implementations (Computational Mathematics Library) - Image 1

Out of stock

This item is currently unavailable

Majosta Numerical Linear Algebra: Theorems, Proofs, and Python Implementations (Computational Mathematics Library)

Name: Numerical Linear Algebra: Theorems, Proofs, and Python Implementations (Computational Mathematics Library)
Brand: Majosta

Languages

Gone for 31 days. Could come back at any time — we're watching for you.

Out of stock 31 days · last price £113 · longest previous gap was 1 days

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 304 days · 165 data points (no recent data)

Historical

Generating forecast…

Price Distribution

Price distribution over 304 days • 1 price levels

Days at Price

Price Analysis

Most common price: £113 (165 days, 100.0%)

Price range: £113 - £113

Price levels: 1 different prices over 165 days

Description

A graduate-level reference that unites rigorous mathematics with hands-on computation. Twenty-four tightly written chapters carry the reader from floating-point arithmetic to large-scale parallel solvers, always pairing theorems and proofs with annotated Python code. Why this book? • Comprehensive coverage of LU and Cholesky factorization, QR decomposition, and Singular Value Decomposition (SVD) – the staples of every scientific computing and machine learning stack. • Complete treatments of iterative methods such as Conjugate Gradient, GMRES, and Lanczos-based eigenvalue algorithms, including advanced preconditioning strategies. • Up-to-date material on randomized linear algebra, low-rank approximation, and sketching – indispensable for modern data science pipelines. • Detailed chapters on GPU acceleration, communication-avoiding algorithms, and distributed memory implementations, giving readers a clear path from theory to high-performance code. • In-depth discussion of condition numbers, backward error analysis, and stability, providing the mathematical guarantees demanded in engineering and quantitative finance. • Every chapter closes with ready-to-run Python notebooks that reproduce all numerical examples and visualizations. Key contents Vector norms, spectral radius, and condition numbers IEEE floating-point and roundoff analysis Backward stability of Gaussian elimination Blocked and communication-optimal LU, QR, and Cholesky Least-squares, Tikhonov regularization, and linear regression Power, inverse, and Rayleigh quotient iterations for eigenvalues Bidiagonal SVD algorithms and sensitivity results Krylov subspace methods – CG, MINRES, GMRES, BiCGStab Preconditioning, algebraic multigrid, and spectral transformations Matrix functions – exponential, logarithm, and fractional powers Low-rank approximation for data compression and machine learning Randomized matrix multiplication, CUR, and RSVD

Product Specifications

Brand: Majosta
Format: hardcover
ASIN: B0FLC5TLSX
Category: Books > Subjects > Computing & Internet > Programming > Languages
Domain: Amazon UK
Release Date: 05 August 2025
Listed Since: 06 August 2025

Barcode

No barcode data available

Majosta Numerical Linear Algebra: Theorems, Proofs, and Python Implementations (Computational Mathematics Library)

Gone for 31 days. Could come back at any time — we're watching for you.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Krylov Methods for Nonsymmetric Linear Systems: From Theory to Computations: 57 (Springer Series in Computational Mathematics, 57)

Guaranteed Accuracy in Numerical Linear Algebra: 252 (Mathematics and Its Applications, 252)

Krylov Subspace Methods for Linear Systems: Principles of Algorithms: 60 (Springer Series in Computational Mathematics, 60)

Numerical Linear Algebra with Applications: Using MATLAB and Octave

Krylov Methods for Nonsymmetric Linear Systems: From Theory to Computations: 57 (Springer Series in Computational Mathematics, 57)

Introduction to Numerical Linear Algebra (Other Titles in Applied Mathematics)

Numerical Linear Algebra and Matrix Factorizations: 22 (Texts in Computational Science and Engineering, 22)

Numerical Linear Algebra and Matrix Factorizations: 22 (Texts in Computational Science and Engineering, 22)

Numerical Linear Algebra, Digital Signal Processing and Parallel Algorithms: 70 (NATO ASI Subseries F:, 70)

Iterative Krylov Methods for Large Linear Systems: 13 (Cambridge Monographs on Applied and Computational Mathematics, Series Number 13)

Krylov Solvers for Linear Algebraic Systems: Krylov Solvers (Volume 11) (Studies in Computational Mathematics, Volume 11)

Numerical Linear Algebra with Applications: Using MATLAB and Octave

Fundamentals of Matrix Computations (Pure and Applied Mathematics: A Wiley Series of Texts, Monographs and Tracts)

Separable Type Representations of Matrices and Fast Algorithms: Volume 1 Basics. Completion Problems. Multiplication and Inversion Algorithms: 234 (Operator Theory: Advances and Applications, 234)

Applied Numerical Linear Algebra (Classics in Applied Mathematics)

High Performance Algorithms for Structured Matrix Problems (Advances in the Theory of Computation and Computational Math)

Introduction to Matrix Computations (Computer Science and Applied Mathematics)

Jones & Bartlett Linear Algebra With Applications - 9th Edition

Applied Linear Algebra (Undergraduate Texts in Mathematics)

Linear Algebra: An Introductory Approach (Undergraduate Texts in Mathematics)

Springer - Linear Algebra for Beginning Graduate Students

Sintez nechetko-neyronnykh modeley prinyatiya resheniy: Metody i algoritmy sinteza nechetko-neyronnykh modeley prinyatiya resheniy

CRC Press Practical Linear Algebra: A Geometry Toolbox Book

Advanced Linear Algebra for Engineers with MATLAB