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Prompt: In Python language, write a function that applies the logistic sigmoid function to all elements of a NumPy array. Code:   import numpy as np import math import matplotlib.pyplot as plt import pandas as pd   def sigmoid(inputArray):               modifiedArray = np.zeros(len(inputArray))               #YOUR CODE HERE:               return(modifiedArray) def test(): inputs = np.arange(-100, 100, 0.5) outputs = sigmoid(inputs) plt.figure(1) plt.plot(inputs) plt.title('Input') plt.xlabel('Index') plt.ylabel('Value') plt.show() plt.figure(2) plt.plot(outputs,'Black') plt.title('Output') plt.xlabel('Index') plt.ylabel('Value') plt.show() test()

Prompt: In Python language, write a function that applies the logistic sigmoid function to all elements of a NumPy array. Code:   import numpy as np import math import matplotlib.pyplot as plt import pandas as pd   def sigmoid(inputArray):               modifiedArray = np.zeros(len(inputArray))               #YOUR CODE HERE:               return(modifiedArray) def test(): inputs = np.arange(-100, 100, 0.5) outputs = sigmoid(inputs) plt.figure(1) plt.plot(inputs) plt.title('Input') plt.xlabel('Index') plt.ylabel('Value') plt.show() plt.figure(2) plt.plot(outputs,'Black') plt.title('Output') plt.xlabel('Index') plt.ylabel('Value') plt.show() test()

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Prompt: In Python language, write a function that applies the logistic sigmoid function to all elements of a NumPy array.

Code:

 

import numpy as np
import math
import matplotlib.pyplot as plt
import pandas as pd
 
def sigmoid(inputArray):
 
            modifiedArray = np.zeros(len(inputArray))
 
            #YOUR CODE HERE:
 
            return(modifiedArray)

def test():

inputs = np.arange(-100, 100, 0.5)
outputs = sigmoid(inputs)
plt.figure(1)
plt.plot(inputs)
plt.title('Input')
plt.xlabel('Index')
plt.ylabel('Value')
plt.show()
plt.figure(2)
plt.plot(outputs,'Black')
plt.title('Output')
plt.xlabel('Index')
plt.ylabel('Value')
plt.show()

test()
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