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DS-1000 / 488 / Right now, I have my data in a 3D numpy array. If I was to use MinMaxScaler…

Problem

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Problem:

Right now, I have my data in a 3D numpy array. If I was to use MinMaxScaler fit_transform on each matrix of the array, it will normalize it column by column, whereas I wish to normalize entire matrices. Is there anyway to do that?
A:
<code>
import numpy as np
from sklearn.preprocessing import MinMaxScaler
a = np.array([[[1, 0.5, -2], [-0.5,1, 6], [1,1,1]], [[-2, -3, 1], [-0.5, 10, 6], [1,1,1]]])
</code>
result = ... # put solution in this variable
BEGIN SOLUTION
<code>

library

Numpy

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Source and history

upstream_id / Original problem ID
488
task_id
142ab547-e26c-57d6-824d-f9bb8c93b7b8
task_key
default--test--488
task_revision_id
1
config / split
default / test

Official source

initial import