from scipy.special import expit 
import numpy as np

def sigmoid(z):
#SIGMOID Compute sigmoid functoon
#   J = SIGMOID(z) computes the sigmoid of z.

    # You need to return the following variables correctly 
    g = np.zeros(z.shape)

# ====================== YOUR CODE HERE ======================
# Instructions: Compute the sigmoid of each value of z (z can be a matrix,
#               vector or scalar).

    # g = 1/(1 + np.exp(-z))
    g = expit(z)

    return g

# =============================================================
from scipy.special import expit 
import numpy as np

def sigmoid(z):
#SIGMOID Compute sigmoid functoon
#   J = SIGMOID(z) computes the sigmoid of z.

    # You need to return the following variables correctly 
    g = np.zeros(z.shape)

# ====================== YOUR CODE HERE ======================
# Instructions: Compute the sigmoid of each value of z (z can be a matrix,
#               vector or scalar).

    # g = 1/(1 + np.exp(-z))
    g = expit(z)

    return g

# =============================================================
#SIGMOID Compute sigmoid functoon #   J = SIGMOID(z) computes the sigmoid of z. # You need to return the following variables correctly # ====================== YOUR CODE HERE ====================== # Instructions: Compute the sigmoid of each value of z (z can be a matrix, #               vector or scalar). # g = 1/(1 + np.exp(-z)) # =============================================================