3D np.array normalization



    The code calculates the shape of the dataset, then reshapes it so that it has the same number of samples and rows as the input dataset.

    Library: numpy

    from sklearn import preprocessing
    samples_count, rows_count, columns_count = dataset.shape
    dataset = dataset.reshape((samples_count, rows_count * columns_count))
    dataset = preprocessing.StandardScaler().fit_transform(dataset)
    dataset = dataset.reshape(samples_count, rows_count, columns_count)
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