Cargando…
Applying Math with Python Over 70 Practical Recipes for Solving Real-World Computational Math Problems.
The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX. You'll start by...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing, Limited,
2022.
|
| Edición: | 2nd ed. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
| LEADER | 00000cam a2200000Mu 4500 | ||
|---|---|---|---|
| 001 | OR_on1352968438 | ||
| 003 | OCoLC | ||
| 005 | 20231017213018.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 221203s2022 xx o ||| 0 eng d | ||
| 040 | |a EBLCP |b eng |c EBLCP |d ORMDA |d OCLCF |d TEFOD |d IEEEE |d OCLCO | ||
| 019 | |a 1354623282 |a 1368202911 | ||
| 020 | |a 9781804616802 | ||
| 020 | |a 180461680X | ||
| 020 | |z 9781804618370 | ||
| 029 | 1 | |a AU@ |b 000074213105 | |
| 035 | |a (OCoLC)1352968438 |z (OCoLC)1354623282 |z (OCoLC)1368202911 | ||
| 037 | |a 9781804618370 |b O'Reilly Media | ||
| 037 | |a 10162904 |b IEEE | ||
| 050 | 4 | |a QA76.95 | |
| 082 | 0 | 4 | |a 510.285/536 |2 23/eng/20221213 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Morley, Sam. | |
| 245 | 1 | 0 | |a Applying Math with Python |h [electronic resource] : |b Over 70 Practical Recipes for Solving Real-World Computational Math Problems. |
| 250 | |a 2nd ed. | ||
| 260 | |a Birmingham : |b Packt Publishing, Limited, |c 2022. | ||
| 300 | |a 1 online resource (376 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Description based upon print version of record. | ||
| 505 | 0 | |a Cover -- Title Page -- Copyright -- Dedication -- Contributors -- Table of Contents -- Preface -- Chapter 1: An Introduction to Basic Packages, Functions, and Concepts -- Technical requirements -- Exploring Python numerical types -- Decimal type -- Fraction type -- Complex type -- Understanding basic mathematical functions -- Diving into the world of NumPy -- Element access -- Array arithmetic and functions -- Useful array creation routines -- Higher-dimensional arrays -- Working with matrices and linear algebra -- Basic methods and properties -- Matrix multiplication | |
| 505 | 8 | |a Determinants and inverses -- Systems of equations -- Eigenvalues and eigenvectors -- Sparse matrices -- Summary -- Further reading -- Chapter 2: Mathematical Plotting with Matplotlib -- Technical requirements -- Basic plotting with Matplotlib -- Getting ready -- How to do it... -- How it works... -- There's more... -- Adding subplots -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Plotting with error bars -- Getting ready -- How to do it... -- How it works... -- There's more... -- Saving Matplotlib figures -- Getting ready -- How to do it... -- How it works... | |
| 505 | 8 | |a There's more... -- See also -- Surface and contour plots -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Customizing three-dimensional plots -- Getting ready -- How to do it... -- How it works... -- There's more... -- Plotting vector fields with quiver plots -- Getting ready -- How to do it... -- How it works... -- There's more... -- Further reading -- Chapter 3: Calculus and Differential Equations -- Technical requirements -- Primer on calculus -- Working with polynomials and calculus -- Getting ready -- How to do it... -- How it works... -- There's more... | |
| 505 | 8 | |a See also -- Differentiating and integrating symbolically using SymPy -- Getting ready -- How to do it... -- How it works... -- There's more... -- Solving equations -- Getting ready -- How to do it... -- How it works... -- There's more... -- Integrating functions numerically using SciPy -- Getting ready -- How to do it... -- How it works... -- There's more... -- Solving simple differential equations numerically -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Solving systems of differential equations -- Getting ready -- How to do it... -- How it works... | |
| 505 | 8 | |a There's more... -- Solving partial differential equations numerically -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Using discrete Fourier transforms for signal processing -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Automatic differentiation and calculus using JAX -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Solving differential equations using JAX -- Getting ready -- How to do it... -- How it works... -- See also -- Further reading | |
| 500 | |a Chapter 4: Working with Randomness and Probability | ||
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX. You'll start by refreshing your knowledge of several core mathematical fields and learn about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you progress, you'll gradually get to grips with more advanced topics of calculus, probability, and networks (graph theory). Once you've developed a solid base in these topics, you'll have the confidence to set out on math adventures with Python as you explore Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Mathematics |x Data processing. | |
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 6 | |a Mathématiques |x Informatique. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 7 | |a Mathematics |x Data processing |2 fast | |
| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Morley, Sam |t Applying Math with Python |d Birmingham : Packt Publishing, Limited,c2022 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781804618370/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL30279151 | ||
| 994 | |a 92 |b IZTAP | ||