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A collection of equations with linear relationships between the variables is known as a system of linear equations. The objective is to identify the values of the variables that concurrently satisfy each equation, each of which is a linear constraint. By figuring out the system, we can learn how the variables interact and find hidden relationships or patterns. In disciplines including physics, engineering, economics, and computer science, it has a wide range of applications. Systems of linear equations can be solved quickly and with accurate results by using methods like Gaussian elimination, matrix factorization, inverse matrices and Lagrange function.
This is implemetations part of Data Science | Solving Linear Equations
Generalized linear equations are represented as below:
Ax=b
Where,
In general, there are three cases one needs to understand:
Consider the system of linear equation:
Output:
Rank of the matrix is: 2 Inverse of A: [[-7. 3.] [ 5. -2.]] Solution of linear equations: [-19. 15.] array([-19., 15.])
Consider the system of linear equation:
Output:
'infinite solution'
Consider the system of linear equation:
Output:
array([15., -5.])
Output:
array([ 5., 10., 15.])
Consider the system of linear equation:
Output:
array([2.22222222, 0.55555556])
Output:
array([ 3.88888889, 11.11111111, 14.44444444])
Consider the system of linear equation:
Output:
array([2., 3., 4.])
Output:
array([20., 38.])
Consider the system of linear equation:
Output:
array([0.36021505, 1.01075269, 4.12365591])
Output:
array([23., 35.])