# Element-Wise Multiplication in NumPy Element-wise multiplication, also known as the Hadamard Product is the multiplication of every element in a matrix by its corresponding element on a secondary matrix.

To perform element-wise matrix multiplication in NumPy, use either the `np.multiply()` function or the `*` (asterisk) character. These operations must be performed on matrices of the same dimension.

## Python Matrix Element-Wise Multiplication with np.multiply()

To multiply matrices, pass them as arguments to `np.multply()` and it will return a new matric containing the result.

``````import numpy as np

m1 = np.array([[2,6,3,9,20],[43,35,28,3,7]])
m2 = np.array([[5,16,4,14,22],[18,8,19,3,3]])

print(np.multiply(m1,m2))
``````
``````[[ 10  96  12 126 440]
[774 280 532   9  21]]
``````

## Element-Wise Multiplication On Specific Rows and Columns

To perform the multiplication on specific rows or columns specify them when passing the matrices into np.multiply() like this:

``````import numpy as np

m1 = np.array([[2,6,3,9,20],[43,35,28,3,7]])
m2 = np.array([[5,16,4,14,22],[18,8,19,3,3]])

print(np.multiply(m1[0,:],m2[0,:]))
``````
``````[ 10  96  12 126 440]
``````

Here is another example specifying columns to multiply:

``````import numpy as np

m1 = np.array([[2,6,3,9,20],[43,35,28,3,7]])
m2 = np.array([[5,16,4,14,22],[18,8,19,3,3]])

print(np.multiply(m1[:,2],m2[:,0]))
``````
``````[ 15 504]
``````

## Multiply Matrices in Python with the * Operator

The native Python `*` (asterisk) operator will perform element-wise multiplication of matrices and return a new matrix containing the result.

``````import numpy as np

m1 = np.array([[2,6,3,9,20],[43,35,28,3,7]])
m2 = np.array([[5,16,4,14,22],[18,8,19,3,3]])

print(m1 * m2)
``````
``````[[ 10  96  12 126 440]
[774 280 532   9  21]]
``````

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