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numpy-exercises

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Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object and tools for working with these arrays. It is the fundamental package for scientific computing with Python. Besides its obvious scientific uses, Numpy can also be used as an efficient multi-dimensional container of generic data.

  • Updated Dec 9, 2022
  • Jupyter Notebook

This repository will be the training documentation and "cheat sheets" I create for myself, my students, and any projects I need to work in. Documentation is KEY - and ensuring you utilize your knowledge solidifies it. So this is a mixture of both.

  • Updated Nov 20, 2022
  • Jupyter Notebook

It includes the basic and advance numpy array manipulations. The topics like indexing, slicing, fast element array-wise functions, mathematical and statistical methods, filing, linear algebra functions, pseudo-random numbers, reshaping, splitting, concatenating,tiles, repeating, where( ) function & numpy advanced array manipulation are implemented.

  • Updated May 28, 2021
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NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object sophisticated (broadcasting) functions tools for integrating C/C++ and Fortran code useful linear algebra, Fourier transform, and random number capabilities

  • Updated Jan 22, 2024
  • Jupyter Notebook

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