I came across this term as I was exploring the different functionalities of NumPy. The term itself means *subtracting the mean of each row from each element of the corresponding row in a matrix* which I completely understand what are we trying to do and can visualize in my head, though I can’t make out the logic in my head to type out code for it, can anyone help out in this?

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Sure @safiaa.02, here is an example code that uses the technique of `NumPy vectorization`

to achieve the task you explained:

- NumPy vectorization is a technique to perform mathematical operations on an array in a faster and more efficient way, by operating on the entire array rather than individual elements.
- In this example code, the mean of each row of a 3x3 matrix is calculated using
`np.mean()`

. Then, NumPy vectorization is used to subtract the row means from each element in the row by adding a new axis to`row_means`

with`[:, np.newaxis]`

.

I hope this code is useful and helps you understand the logic of this technique in code!