Hello guys. How are you all? I hope you all fine. In this tutorial we will learn about Numpy dot vs matmul in Python. so without wasting time lets learn about of this.

## Numpy dot vs matmul in Python

**Numpy dot vs matmul in Python**to Numpy dot vs matmul in Python use this method. By using this method you can Numpy dot vs matmul in Python. It is very easy to use. Lets learn about of this by given below example:

Output :`import numpy as np arr1 = np.array([[3,2],[5,3]]) arr2 = np.array(([4,6],[4,7])) print(np.dot(arr1,arr2)) print(arr1@arr2)`

**[[20 32] [32 51]] [[20 32] [32 51]]****Numpy dot vs matmul in Python**to Numpy dot vs matmul in Python use this method. By using this method you can Numpy dot vs matmul in Python. It is very easy to use. Lets learn about of this by given below example:

Output :`import numpy as np arr1 = np.array([[4,5,6], [3,2,1], [1, 2, 3]]) arr2 = np.array([[[6,7,8], [7,8,9], [1, 2, 3]]]) print("vector multiplication") print(np.dot(arr1, arr2))`

`[[[65 80 95]] [[33 39 45]] [[23 29 35]]]`

**np matmul**To Numpy dot vs matmul in Python use this method. By using this method you can Numpy dot vs matmul in Python. It is very easy to use. Lets learn about of this by given below example:

Output :`[[[65 80 95]] [[33 39 45]] [[23 29 35]]]`

## Method 1:

It is very easy to use. Lets learn about of this by given below example:

```
import numpy as np
arr1 = np.array([[3,2],[5,3]])
arr2 = np.array(([4,6],[4,7]))
print(np.dot(arr1,arr2))
print(arr1@arr2)
```

Output :

```
[[20 32]
[32 51]]
[[20 32]
[32 51]]
```

## Method 2:

It is very easy to use. Lets learn about of this by given below example:

```
import numpy as np
arr1 = np.array([[4,5,6], [3,2,1], [1, 2, 3]])
arr2 = np.array([[[6,7,8], [7,8,9], [1, 2, 3]]])
print("vector multiplication")
print(np.dot(arr1, arr2))
```

Output :

```
[[[65 80 95]]
[[33 39 45]]
[[23 29 35]]]
```

**Conclusion**

It’s all About this Tutorial. Hope all methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which method worked for you?

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