*Mathematics is universal**. Machine Learning is built on top of mathematical prerequisites such as **Linear Algebra, Probability and Statistics**. We shall now see the implementation of the basic underlying mathematical concepts in each of these prerequisites using Python.*

A branch of mathematics that is concerned with mathematical structures closed under the operations of *addition* and *scalar multiplication* and that includes the theory of systems of linear equations, matrices, determinants, vector spaces, and linear transformations — *Source: **Merriam Webster*

*If you haven’t gone through — **Getting Familiar with Numpy**, **make sure to go through it! We’ll be needing Numpy in implementing most of the Math concepts!*

## Getting Started

Libraries you’ll be needing to import for this tutorial — *Numpy**, **Matplotlib** and Scipy*

`import numpy as np`

import matplotlib.pyplot as plt

import scipy.linalg as la

%matplotlib inline

*Let’s compute** 2I+3A−AB** (I is the identity matrix of size 2) for —*