import numpy as np

def standardize(x, myMean = None, myStd = None):
    ''' fill your code in here...
    '''
    if not myMean:
        myMean = np.mean(x, axis=0)
    centered_data = x - myMean
    if not myStd:
        myStd = np.std(centered_data, axis=0)
    
    std_data = centered_data / myStd
    
    return std_data, myMean, myStd
7c51f829f4e0a7756f43d143f6d6f088fca146bf
<mask token>

<mask token>


def standardize(x, myMean=None, myStd=None):
    """ fill your code in here...
    """
    if not myMean:
        myMean = np.mean(x, axis=0)
    centered_data = x - myMean
    if not myStd:
        myStd = np.std(centered_data, axis=0)
    std_data = centered_data / myStd
    return std_data, myMean, myStd

import numpy as np


def standardize(x, myMean=None, myStd=None):
    """ fill your code in here...
    """
    if not myMean:
        myMean = np.mean(x, axis=0)
    centered_data = x - myMean
    if not myStd:
        myStd = np.std(centered_data, axis=0)
    std_data = centered_data / myStd
    return std_data, myMean, myStd

import numpy as np

def standardize(x, myMean = None, myStd = None):
    ''' fill your code in here...
    '''
    if not myMean:
        myMean = np.mean(x, axis=0)
    centered_data = x - myMean
    if not myStd:
        myStd = np.std(centered_data, axis=0)
    
    std_data = centered_data / myStd
    
    return std_data, myMean, myStd