Name: Linear Algebra with Python
Price: 63 CHF
Availability: InStock
ISBN: 9789819929504

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Zurich

Lausanne

Wohlen

Basel

Kriens

Winterthur

Bern

Dietikon

St. Gallen

Geneva

Springer

This textbook is aimed at those who wish to learn linear algebra from the ground up. After a brief mathematical introduction, it provides the standard curriculum of linear algebra based on an abstract linear space. It covers various aspects including linear transformations and their matrix representations, basis and dimension, matrix invariants, inner products and norms, eigenvalues and eigenvectors, as well as Jordan normal forms. Detailed and independent proofs and descriptions are provided for all theorems, formulas, and algorithms.

A unified overview of linear structures is presented through the development of linear algebra from the perspective of functional analysis. Advanced topics such as functional analyses, 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 are addressed. All of this provides a bridge to more specialized theories based on linear algebra in mathematics, physics, engineering, economics, and social sciences.

Throughout the book, Python is used to explain linear algebra. Through interactive learning with Python, readers naturally become accustomed to programming in Python. With Python libraries such as NumPy, Matplotlib, VPython, and SymPy, readers can easily perform large-scale matrix computations, visualize calculation results, and carry out symbolic calculations. All codes in this book can be executed on both Windows and macOS, as well as on Raspberry Pi.

Actual product image Linear Algebra with Python (English, Hardcover, Hiroshi Kaneko, Kiyoshi Shirayanagi, Makoto Tsukada, Masato Noguchi, Sin-Ei Takahasi, Yuji Kobayashi)

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