In this article, you will learn how to create dot product of two arrays in using numpy.dot() function.

**Syntax:** numpy.dot(a, b, out=None)

Dot product of two arrays. Specifically,

If both a and b are 1-D arrays, it is inner product of vectors (without complex conjugation).

If both a and b are 2-D arrays, it is matrix multiplication, but using matmul or a @ b is preferred.

If either a or b is 0-D (scalar), it is equivalent to multiply and using numpy.multiply(a, b) or a * b is preferred.

If a is an N-D array and b is a 1-D array, it is a sum product over the last axis of a and b.

If a is an N-D array and b is an M-D array (where M>=2), it is a sum product over the last axis of a and the second-to-last axis of b:

dot(a, b)[i,j,k,m] = sum(a[i,j,:] * b[k,:,m])

**Parameters: **

a : array_like

First argument.

b : array_like

Second argument.

out : ndarray, optional

Output argument. This must have the exact kind that would be returned if it was not used. In particular, it must have the right type, must be C-contiguous, and its dtype must be the dtype that would be returned for dot(a,b). This is a performance feature. Therefore, if these conditions are not met, an exception is raised, instead of attempting to be flexible.

**Returns: **

output : ndarray

Returns the dot product of a and b. If a and b are both scalars or both 1-D arrays then a scalar is returned; otherwise an array is returned. If out is given, then it is returned.

**Raises: **

ValueError

If the last dimension of a is not the same size as the second-to-last dimension of b.

**#example program on np.dot() function**

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```
import numpy as np
print('single array result\n',np.dot(3, 4))
# two dimentionl array
a=np.array([[1, 2], [ 5, 6]])
b=np.array([[1, 4], [ 5, 8]])
print(a.shape)
print(b.shape)
c=np.dot(a,b)
print('two dimentionl arrayresult\n',c)
# three dimentionl array
a=np.array([[1, 2,3], [4, 5, 6], [7,8,9]])
b=np.array([[1, 2,3], [4, 5, 6], [7,8,9]])
print(a.shape)
print(b.shape)
c=np.dot(a,b)
print('three dimentionl arrayresult\n',c)
```

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