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| fixed length control field |
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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
241114b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9789819929504 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
512.502855133 |
| Item number |
TSU |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Tsukada, Makoto |
| 245 ## - TITLE STATEMENT |
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| Title |
Linear Algebra with Python : theory and applications |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Springer, |
| Date of publication, distribution, etc |
2023 |
| Place of publication, distribution, etc |
Singapore : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xv, 308 p. ; |
| Other physical details |
ill., |
| Dimensions |
27 cm. |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
4077.00 |
| Price type code |
₹ |
| Unit of pricing |
01 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
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. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Algebra, Linear |
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| Topical term or geographic name as entry element |
Fourier Analysis |
|
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| Topical term or geographic name as entry element |
Functional analysis and transforms |
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| Topical term or geographic name as entry element |
Mathematics Applied |
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| Topical term or geographic name as entry element |
Maths for engineers |
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| Topical term or geographic name as entry element |
Maths for scientists |
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| Topical term or geographic name as entry element |
Wavelets |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Kobayashi, Yuji |
|
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| Personal name |
Kaneko, Hiroshi |
|
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| Personal name |
Takahasi, Sin-Ei |
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| Personal name |
Shirayanagi, Kiyoshi |
|
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| Personal name |
Noguchi, Masato |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |