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Learn numpy quickly

Crystal X
22 min readFeb 19, 2023

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I have been studying python within the context of data science for over two years now, so I thought it would be a good idea to consolidate all of the information that I have regarding this programming language. In this blog post, therefore, I will be discussing Python’s numerical library, numpy, which is one library that is necessary when carrying out data science projects.

NumPy was first created in 2005 by Travis Oliphant as an open-source numerical computing library for Python. Since then, it has become one of the most popular and widely used libraries for numerical computing in Python.

NumPy is an open-source numerical computing library for Python that provides a powerful set of tools for working with arrays and matrices. It is one of the fundamental building blocks of scientific computing in Python, and it is used extensively in fields such as physics, engineering, data science, and machine learning.

At its core, NumPy provides a fast and efficient implementation of multi-dimensional arrays and matrices in Python. These arrays are much more efficient than traditional Python lists, both in terms of memory usage and computational speed. NumPy also provides a rich set of functions for performing mathematical operations on these arrays, including linear algebra, Fourier transforms, random number generation, and more.

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Crystal X
Crystal X

Written by Crystal X

I have over five decades experience in the world of work, being in fast food, the military, business, non-profits, and the healthcare sector.

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