Livrare gratuită pentru comenzile peste 349,00 lei.

Verifică starea comenzii

Faceți parte dintr-o comunitate de iubitori de cărți din întreaga lume și beneficiați de o mulțime de avantaje Creați-vă un cont gratuit

Transport gratuit la punctele de livrare Pick Up peste 349.00 lei

Packeta 15.00 lei Cargus 28.00 lei Easybox 20.00 lei FAN 20.00 lei Punct FAN 16.00 lei Punct DPD 17.00 lei Curier Sameday 24.00 lei Curier DPD 25.00 lei

Contact

Cum să cumpăr

Ajutor

Contul meu

▸ Gol :-(

Livrare gratuită pentru comenzile peste 349,00 lei.

Linear Algebra with Python

Name: Linear Algebra with Python
Brand: Springer Nature Singapore
SKU: 47031907
Price: 335.46 RON
Availability: InStock
Author: Yuji Kobayashi
ISBN: 9789819929535

Limba

engleză

Carte Carte broșată

Codul Libristo: 47031907

Editura Springer Nature Singapore, decembrie 2024

This textbook is for those who want to learn linear algebra from the basics. After a brief mathemati... Descrierea completă

Codul Libristo: 47031907

155 b

335.46 lei

În depozitul extern Expediem în 5-8 zile

30 de zile pentru retur bunuri

Clienții au cumpărat de asemenea

Exploring University Mathematics with Python Siri Chongchitnan

Copertă tare

390.96 lei

Mathematische Werke Karl Weierstrass

Carte broșată

336.71 lei

Elítéltek B. E. Belle

Carte broșată

94.95 lei

The Group for Mutual Improvement Jordan Baumgarten

Copertă tare

231.34 lei

L'Homme spatial Michel Lussault

Carte broșată

158.46 lei

Guantes manoplas y mitones de punto nº 10 VERONICA HUG

Carte broșată

44.87 lei

My First Words Spanish: Mis primeras palabras en Espa?ol - Bilingual children's books Spanish English, Spanish for Toddlers Felipe Fernandez

Carte broșată

71.73 lei

Georges Pompidou, Directeur de Cabinet Du General de Gaulle Bernard Lachaise

Carte broșată

221.56 lei

This textbook is for those who want to learn linear algebra from the basics. After a brief mathematical introduction, it provides the standard curriculum of linear algebra based on an abstract linear space. It covers, among other aspects: linear mappings and their matrix representations, basis, and dimension; matrix invariants, inner products, and norms; eigenvalues and eigenvectors; and Jordan normal forms. Detailed and self-contained proofs as well as descriptions are given for all theorems, formulas, and algorithms.

A unified overview of linear structures is presented by developing linear algebra from the perspective of functional analysis. Advanced topics such as function space are taken up, along with Fourier analysis, the Perron-Frobenius theorem, linear differential equations, the state transition matrix and the generalized inverse matrix, singular value decomposition, tensor products, and linear regression models. These all provide a bridge to more specialized theories based on linear algebra in mathematics, physics, engineering, economics, and social sciences.

Python is used throughout the book to explain linear algebra. Learning with Python interactively, readers will naturally become accustomed to Python coding. By using Python's libraries NumPy, Matplotlib, VPython, and SymPy, readers can easily perform large-scale matrix calculations, visualization of calculation results, and symbolic computations. All the codes in this book can be executed on both Windows and macOS and also on Raspberry Pi.