The whole preceding process is implemented in code as follows: 

1. Import relevant classes within a package:

from scipy import linalg 

2. Initialize the right-hand side and left-hand side matrices (input and output matrices):

A=[[1,3,5],[2,5,1],[2,3,8]]
b=[[10],[8],[3]] 

Now, we will look into the function used to solve the equation A*x = b.

Method 1 (using the functions we have learnt so far)

Multiply the inverse of A with b.

np.dot(linalg.inv(A),b)

Method 2 (using the solve function)

Using the solve function within the scipy package helps in solving the equation straight away:

scipy.linalg.solve(x, b)

The output of either of the preceding methods is the solution, as follows: 

array([[-9.28],       [ 5.16],       [ 0.76]])

Calculating the determinant of a matrix

As seen earlier, in order to solve a linear system, we need to calculate the inverse of a matrix first, which in turn requires us to calculate the determinant of the matrix. 

The way in which the determinant is calculated is as follows:

The determinant of a matrix in Python can be calculated by using the det function in scipy.linalg.

The same preceding calculation can be implemented in code, as follows:

linalg.det(A)