Python Numpy an introduction

Python Numpy an introduction

In order to implement projects and make models on machine learning ,one of the most important libraries in python is numpy. Numpy is useful for creating arrays to hold scientific data and other high level mathematical functions. Though we have list data structure but it is flexible to be used in data science and machine learning models, they turn out to be slow. Also  numpy is useful for linear algebra, Fourier transform ,and random number capabilities.

In order to use numpy it is recommended that a user should use scientific python development. For many users, especially on Windows, the easiest way to begin is to download Anaconda which include all the key packages and notebooks like jupyter,spyder,scipy,pandas,dask,Bokeh,HoloViews,Datashader,matplotlib,,tensorflow,conda and many more(1500+). Installing it is also very easy. Go to javascript:nicTemp(); (its for windows os, for linux or macOS , select the os first) and download the python3.x version and simply install it following instructions alongside,just like you install other softwares in your pc. If you want to know more go to javascript:nicTemp();

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