Linear algebra : theory, intuition, code
"Linear algebra is perhaps the most important branch of mathematics for computational sciences, including machine learning, AI, data science, statistics, simulations, computer graphics, multivariate analyses, matrix decompositions, signal processing, and so on. The way linear algebra is present...
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| Hlavní autor: | |
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| Médium: | Kniha |
| Jazyk: | angličtina |
| Vydáno: |
[Spojené státy americké?] :
SincXpress,
2021
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| Žánr/forma: | monografie |
| ISBN: | 978-90-831366-0-8 |
| Témata: | |
| Tagy: |
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| Shrnutí: | "Linear algebra is perhaps the most important branch of mathematics for computational sciences, including machine learning, AI, data science, statistics, simulations, computer graphics, multivariate analyses, matrix decompositions, signal processing, and so on. The way linear algebra is presented in traditional textbooks is different from how professionals use linear algebra in computers to solve real-world applications in machine learning, data science, statistics, and signal processing. For example, the "determinant" of a matrix is important for linear algebra theory, but should you actually use the determinant in practical applications? The answer may surprise you! If you are interested in learning the mathematical concepts linear algebra and matrix analysis, but also want to apply those concepts to data analyses on computers (e.g., statistics or signal processing), then this book is for you. You'll see all the math concepts implemented in MATLAB and in Python."--Nakladatelská anotace |
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| Fyzický popis: | 589 stran : ilustrace ; 25 cm |
| Bibliografie: | Obsahuje bibliografické odkazy a rejstřík |
| Vydání: | Book edition 1. |