Matrix inverse (inv) in SciPy - Mini Project: Build & Apply

Matrix inverse (inv)

📖 Scenario: You work as a data analyst and need to solve a system of equations using matrix operations. One important step is to find the inverse of a matrix.

🎯 Goal: Learn how to create a matrix using numpy and find its inverse using scipy.linalg.inv.

📋 What You'll Learn

Create a 2x2 matrix using numpy.array with exact values

Import the inv function from scipy.linalg

Calculate the inverse of the matrix using inv

Print the inverse matrix

💡 Why This Matters

🌍 Real World

Matrix inversion is used in many fields like engineering, physics, and computer science to solve systems of equations and transform data.

💼 Career

Knowing how to invert matrices is important for data analysts and scientists working with linear algebra problems and machine learning algorithms.

1

Create the matrix

Create a variable called matrix and assign it a 2x2 numpy array with these exact values: [[4, 7], [2, 6]].

SciPy

# Your code here

Need a hint?

Use np.array to create the matrix with the exact values.

2

Import the inverse function

Import the inv function from scipy.linalg.

SciPy

import numpy as np
matrix = np.array([[4, 7], [2, 6]])
# Your code here

Need a hint?

Use from scipy.linalg import inv to import the inverse function.

3

Calculate the inverse matrix

Create a variable called inverse_matrix and assign it the inverse of matrix using the inv function.

SciPy

import numpy as np
matrix = np.array([[4, 7], [2, 6]])
from scipy.linalg import inv
# Your code here

Need a hint?

Use inv(matrix) to calculate the inverse.

4

Print the inverse matrix

Print the variable inverse_matrix to display the inverse matrix.

SciPy

import numpy as np
matrix = np.array([[4, 7], [2, 6]])
from scipy.linalg import inv
inverse_matrix = inv(matrix)
# Your code here

Need a hint?

Use print(inverse_matrix) to show the result.