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Advanced Mathematical Numpy Funtions

Welcome to my numpy practice notebook.

Numpy is a very nice python library for performing mathematical computations in a very short of time. Numpy has a very large number of functions, modules and classes inside it. You can start reading about numpy here and if you are a very beginner to understand mathematical problems and their solutions using numpy just visit here this will really give you essence of mathematical computation using python numpy library.

The funtions that I have picked up for showing my understanding of numpy mathematical funtions have a deeper domain of mathematics, these are from graduation calculus and algebra. And these functions are often being used in background of functions from Machine Learning libraries for doing gradient decent and array operations. There we have lots of non-linear activation functions each of these such functions carrys a lot of mathematical calculations and these calculations are being processed by those activation functions behind the scene, and this makes our work much easier than writing codes for those calculations ourself.

  • numpy.diff()
  • numpy.power()
  • numpy.linalg.norm()
  • numpy.polynomial.legendre.Legendre()
  • numpy.polynomial.polynomial.Polynomial()

The recommended way to run this notebook is to click the "Run" button at the top of this page, and select "Run on Binder". This will run the notebook on mybinder.org, a free online service for running Jupyter notebooks.

!pip install jovian --upgrade -q
import jovian
[jovian] Attempting to save notebook.. [jovian] Updating notebook "thakubhai-007/zerotoanalyst-numpy-array-operations" on https://jovian.ai [jovian] Uploading notebook.. [jovian] Uploading additional files... [jovian] Committed successfully! https://jovian.ai/thakubhai-007/zerotoanalyst-numpy-array-operations

Let's begin by importing Numpy and listing out the functions covered in this notebook.