Multiplying matrices is a fundamental operation in linear algebra, and it has many applications in machine learning, computer graphics, and scientific computing.

In this tutorial, we will write a Python program to multiply two matrices using the NumPy library.

First, we need to install NumPy using pip.

Open the command prompt or terminal and run the following command:

pip install numpy

Once we have installed NumPy, we can import it in our Python program using the following line of code:

import numpy as np

Now, let’s define two matrices `A`

and `B`

that we want to multiply:

A = np.array([[1, 2], [3, 4]]) B = np.array([[5, 6], [7, 8]])

We can multiply `A`

and `B`

using the `dot`

function provided by NumPy:

C = np.dot(A, B)

The resulting matrix `C`

will be:

array([[19, 22], [43, 50]])

We can also use the `@`

operator in Python 3.5 or later versions to multiply two matrices:

C = A @ B

This will give us the same result as before:

array([[19, 22], [43, 50]])

In summary, multiplying two matrices in Python using NumPy is a simple and efficient operation that can be done with just a few lines of code.

By using the `dot`

function or the `@`

operator, we can easily perform matrix multiplication in our programs.