Guide to NumPy (Travis E. Oliphant)

 
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Guide to NumPy (Travis E. Oliphant)

A Python plugin called NumPy offers numerical functions and arrays that are highly efficient. Matlab and Mathematica's vectorized operations are largely replaced by NumPy, which, unlike those programs, is free and open source.

Today's scientific and technological world is all about speed and adaptability.

Programmers, scientists, and engineers who are interested in using Python to perform numerical calculations should read this book. You'll get a strong foundation in NumPy arrays and general functions from it. You can use NumPy productively and write clear, quick code by learning NumPy Array.

  • Improve the performance of calculations with clean and efficient NumPy code
  • Analyze large data sets using statistical functions and execute complex linear algebra and mathematical computations
  • Perform complex array operations in a simple manner.

Ebook Details

About the Authors
Travis E. Oliphant is an American data scientist, entrepreneur, and fervent supporter of open-source software. He holds a Ph.D. from the Mayo Clinic as well as B.S. and M.S. degrees in electrical engineering and mathematics from Brigham Young University. He has used Python for scientific and numerical programming frequently since 1997. He was a founding member of the SciPy package and the main developer of the NumPy package.
Published
Published Date / Year
(Dec 7, 2006)
License(s)
Public Domain Mark 1.0
eBook Format
HTML, PDF (371 pages), ePub, Kindle (Mobi), etc.
Language
English

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