Q.39: How to Get the Eigen Values of a Matrix
With the help of np.eigvals() method, we can get the eigen values of a matrix by using np.eigvals() method.
Python
np.eigvals(matrix)
Q.40: How to Calculate the Determinant of a Matrix Using NumPy?
The Determinant of a square matrix is a unique number that can be derived from a square matrix. Using the numpy.linalg.det() method, NumPy gives us the ability to determine the determinant of a square matrix.
Python
numpy.linalg.det(array)
Q.41: Find a Matrix or Vector Norm Using NumPy
We employ the numpy.linalg.norm() method of the NumPy Python library to determine a matrix or vector norm. Depending on the value of its parameters, this function returns either one of the seven matrix norms or one of the infinite vector norms.
Python
numpy.linalg.norm(x, ord=None, axis=None)
Q.43: Calculate the QR Decomposition of a Given Matrix Using NumPy
A matrix’s decomposition into the form “A=QR,” where Q is an orthogonal matrix and R is an upper-triangular matrix, is known as QR factorization. With the aid of numpy, we can determine the QR decomposition of a given matrix using numpy.linalg.qr().
Python
numpy.linalg.qr(a, mode='reduced')