Two matrices are compatible for multiplication if the number of columns of 1 matrix is equal to the number of rows of the other matrix. 

For example, if matrix 1 has dimensions a * N and matrix 2 has dimensions N * b, then the resulting matrix has dimensions of a * b.

The illustration below shows how this is done:



To multiply two matrices use the `dot()` function of NumPy. It takes only 2 arguments and returns the product of two matrices.
# Syntax
The general syntax is :
```python
np.dot(x,y)
```
where x and y are two matrices of size **a * M** and **M * b**, respectively.
# Code
The following code shows an example of multiplying matrices in NumPy:

import numpy as np
# two dimensional arrays
m1 = np.array([[1,4,7],[2,5,8]])
m2 = np.array([[1,4],[2,5],[3,6]])
m3 = np.dot(m1,m2) 
print(m3) 

# three dimensional arrays
m1 = ([1, 6, 5],[3 ,4, 8],[2, 12, 3]) 
m2 = ([3, 4, 6],[5, 6, 7],[6,56, 7]) 
m3 = np.dot(m1,m2) 
print(m3) 


How to multiply matrices in NumPy

Two matrices are compatible for multiplication if the number of columns of 1 matrix is equal to the number of rows of the other matrix. For example, if matrix 1 has dimensions a * N and matrix 2 has dimensions N * b, then the resulting matrix has dimensions of a * b. The illustration below shows how this is done: 