I would like to have the norm of one NumPy array. More specifically, I am looking for an equivalent version of this function
norm = np.linalg.norm(v)
if norm == 0:
return v / norm
Is there something like that in sklearn or NumPy?
This function works in a situation where v is the 0 vector.
The normalization of data is important for the fast and smooth training of our machine learning models. Scikit learns, a library of python has sklearn.preprocessing.normalize, which helps to normalize the data easily.