Challenge: Solving the Task Using SLE | Linear Algebra
Mathematics for Data Analysis and Modeling

Course Content

Mathematics for Data Analysis and Modeling

## Mathematics for Data Analysis and Modeling

1. Basic Mathematical Concepts and Definitions
2. Linear Algebra
3. Mathematical Analysis

# Challenge: Solving the Task Using SLE

We have already considered how to solve the SLE using inversed matrix. But we can also use `np.linalg.solve(A, y)` method that calculates the solution of the SLE:
`A * x = y`.
Your task is to solve the system using both these methods and compare the results:

1. Use `np.linalg.solve()` method.
2. Use `np.inv()` method to calculate inversed matrix and provide solution using: `x = A_inv @ y`.

We have already considered how to solve the SLE using inversed matrix. But we can also use `np.linalg.solve(A, y)` method that calculates the solution of the SLE:
`A * x = y`.
Your task is to solve the system using both these methods and compare the results:

1. Use `np.linalg.solve()` method.
2. Use `np.inv()` method to calculate inversed matrix and provide solution using: `x = A_inv @ y`.

Everything was clear?

Section 2. Chapter 8

# Challenge: Solving the Task Using SLE

We have already considered how to solve the SLE using inversed matrix. But we can also use `np.linalg.solve(A, y)` method that calculates the solution of the SLE:
`A * x = y`.
Your task is to solve the system using both these methods and compare the results:

1. Use `np.linalg.solve()` method.
2. Use `np.inv()` method to calculate inversed matrix and provide solution using: `x = A_inv @ y`.

We have already considered how to solve the SLE using inversed matrix. But we can also use `np.linalg.solve(A, y)` method that calculates the solution of the SLE:
`A * x = y`.
Your task is to solve the system using both these methods and compare the results:

1. Use `np.linalg.solve()` method.
2. Use `np.inv()` method to calculate inversed matrix and provide solution using: `x = A_inv @ y`.

Everything was clear?

Section 2. Chapter 8

# Challenge: Solving the Task Using SLE

We have already considered how to solve the SLE using inversed matrix. But we can also use `np.linalg.solve(A, y)` method that calculates the solution of the SLE:
`A * x = y`.
Your task is to solve the system using both these methods and compare the results:

1. Use `np.linalg.solve()` method.
2. Use `np.inv()` method to calculate inversed matrix and provide solution using: `x = A_inv @ y`.

We have already considered how to solve the SLE using inversed matrix. But we can also use `np.linalg.solve(A, y)` method that calculates the solution of the SLE:
`A * x = y`.
Your task is to solve the system using both these methods and compare the results:

1. Use `np.linalg.solve()` method.
2. Use `np.inv()` method to calculate inversed matrix and provide solution using: `x = A_inv @ y`.

Everything was clear?

We have already considered how to solve the SLE using inversed matrix. But we can also use `np.linalg.solve(A, y)` method that calculates the solution of the SLE:
`A * x = y`.
1. Use `np.linalg.solve()` method.
2. Use `np.inv()` method to calculate inversed matrix and provide solution using: `x = A_inv @ y`.