Numpy : Matrix multiplication using Arrays & Matrices

Numpy, one of the powerful package in Python has Matrices and N-Dimensional Arrays which can be used for matrix computation.

Numpy matrices are basically 2-dimensional arrays, which are subclassed from ndarray having access to all attributes and methods of the super class. Numpy arrays, on the otherhand are N-Dimensional arrays.

For numpy matrices, if we need to obtain matrix multiplication, we will simply use "*" operator.

import numpy as np
a=np.mat('4 3; 2 1')
b=np.mat('1 2; 3 4')
print(a)
# [[4 3]
#  [2 1]]
print(b)
# [[1 2]
#  [3 4]]
print(a*b)
# [[13 20]
#  [ 5  8]]

However, if we use "*" operator on Numpy arrays, we will get the element-wise multiplication

import numpy as np
c=np.array([[4, 3], [2, 1]])
d=np.array([[1, 2], [3, 4]])
print(c*d)
# [[4 6]
#  [6 4]]

To obtain the matrix multiplication using Numpy arrays, we need to do the following

print(np.dot(c,d))
# [[13 20]
#  [ 5  8]]

# OR 

print(a@b)
# [[13 20]
#  [ 5  8]]