content update for arraycomputing ref numpy#43

Author: shaloo

content/en/arraycomputing.md

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+Arrays are a type of data structures that are used to organize vast amounts of data such that related set of values can be easily sorted, searched, mathematically manipulated and transformed easily and quickly. 
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+Array computing has become synonymous with large scale data manipulation.
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+**Array computing** is unique as it involves operating on the data array at once. What this means is that any array operation applies to an entire set of values in one shot.  This vectorized approach provides speed and simplicity by enabling programmers to code and operate on aggregates of data, without having to use loops of individual scalar operations.  It is the foundation of statistical, mathematical, scientific computing and modern day data science analytics. Some real life examples of application of array computing include data visualization, digital signal processing, image processing, bioinformatics, machine learning and AI. 
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+The language of choice for data analytics, machine learning and productive numerical computing is Python.
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+**Num**erical **Py**thon or NumPy is its de-facto standard Python programming language library that supports large, multi-dimensional arrays and matrices, and comes with a vast collection of high-level mathematical functions to operate on these arrays. 
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