# Difference between NumPy.dot() and ‘*’ operation in Python

In Python if we have two numpy arrays which are often referd as a vector. The `'*'` operator and `numpy.dot()` work differently on them. It’s important to know especially when you are dealing with data science or competitive programming problem.

### Working of ‘*’ operator

‘*’ operation caries out element-wise multiplication on array elements. The element at `a[i][j]` is multiplied with `b[i][j]` .This happens for all elements of array.

Example:

```Let the two 2D array are v1 and v2:-
v1 = [[1, 2], [3, 4]]
v2 = [[1, 2], [3, 4]]

Output:
[[1, 4]
[9, 16]]
From below picture it would be clear.``` ### Working of numpy.dot()

It carries of normal matrix multiplication . Where the conditon of number of columns of first array should be equal to number of rows of second array is checked than only `numpy.dot()` function take place else it shows an error.
Example:

```Let the two 2D array are v1 and v2:-
v1=[[1, 2], [3, 4]]
v2=[[1, 2], [3, 4]]
Than numpy.dot(v1, v2)  gives output of :-
[[ 7 10]
[15 22]]```

Examples 1:

 `import` `numpy as np ` ` `  ` `  `# vector v1 of dimension (2, 2) ` `v1 ``=` `np.array([[``1``, ``2``], [``1``, ``2``]]) ` ` `  `# vector v2 of dimension (2, 2) ` `v2 ``=` `np.array([[``1``, ``2``], [``1``, ``2``]]) ` ` `  `print``(``"vector multiplication"``) ` `print``(np.dot(v1, v2)) ` ` `  `print``(``"\nElementwise multiplication of two vector"``) ` `print``(v1 ``*` `v2) `

```Output :
vector multiplication
[[3 6]
[3 6]]

Elementwise multiplication of two vector
[[1 4]
[1 4]]
```

Examples 2:

 `import` `numpy as np ` ` `  ` `  `v1 ``=` `np.array([[``1``, ``2``, ``3``], [``1``, ``2``, ``3``], [``1``, ``2``, ``3``]]) ` ` `  `v2 ``=` `np.array([[[``1``, ``2``, ``3``], [``1``, ``2``, ``3``], [``1``, ``2``, ``3``]]]) ` ` `  `print``(``"vector multiplication"``) ` `print``(np.dot(v1, v2)) ` ` `  `print``(``"\nElementwise multiplication of two vector"``) ` `print``(v1 ``*` `v2) `

```Output :
vector multiplication
[[ 6 12 18]
[ 6 12 18]
[ 6 12 18]]

Elementwise multiplication of two vector
[[1 4 9]
[1 4 9]
[1 4 9]]
```

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