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Numerical Python : Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib (English Edition) de [Robert Johansson]
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Numerical Python : Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib (English Edition) 2nd Edition, Edición Kindle


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Kindle
$683.36
Pasta blanda $592.07

Número de páginas: 700 páginas Idioma: Inglés

Descripción del producto

Descripción del producto

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis. After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning.What You'll Learn
Work with vectors and matrices using NumPy
Plot and visualize data with Matplotlib
Perform data analysis tasks with Pandas and SciPy
Review statistical modeling and machine learning with statsmodels and scikit-learn
Optimize Python code using Numba and Cython
Who This Book Is For

Developers who want to understand how to use Python and its related ecosystem for numerical computing.

Contraportada

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more.

Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis.

After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning.


Detalles del producto

  • Formato: Edición Kindle
  • Tamaño del archivo: 48296 KB
  • Número de páginas: 700
  • Editor: Apress; Edición: 2 (24 de diciembre de 2018)
  • Vendido por: Amazon Mexico Services, Inc.
  • Idioma: Inglés
  • ASIN: B07M5ZDV62
  • Texto a voz: Activado
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5.0 de 5 estrellasExcellent! Worth every penny!
7 de abril de 2019 - Publicado en Amazon.com
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5.0 de 5 estrellasa great scientific computing book
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