Numpy Functions for Linear Algebra

Introducing some of the most common linear algebraic function in Numpy.

When it comes to dealing with numbers arrays and matrices makes our life much easier. And Numpy makes it much more easier. Numpy is a go to library in Python for decalring large and multidimensional arrays. It also has a rich collection of mathimatial and statistical functions that operate on them.

numpy.vdot()
numpy.linalg.inv()
numpy.linalg.matrix_rank()
function 4
function 5

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.commit(project='numpy-array-operations')

[jovian] Detected Colab notebook...
[jovian] Please enter your API key ( from https://jovian.ml/ ):
API KEY: ··········
[jovian] Uploading colab notebook to Jovian...
[jovian] Committed successfully! https://jovian.ml/akahaycpradeep/numpy-array-operations

'https://jovian.ml/akahaycpradeep/numpy-array-operations'

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