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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()arrow_forwardDevelop python program of function randomArray(m, n) that takes two integers as argument and returns a 2D m-by-n array with random elements in it. Develop python program of function adder(a1, a2) that reads two 2D arrays of the same size and returns an array that is the summation of a1 and a2. To add the two arrays, you need to add their elements, correspondingly. Develop a python program of function inverseArray(a) that takes a 2D-array as argument and inverses the array. You will need to inverse the rows, first and then inverse the columns, next. For instance, if the array = [[2, 3, 4], [5, 6, 7]], the inverse will be = [[7, 6, 5], [4, 3, 2]]arrow_forwardProblem2: A square matrix can be represented by a two-dimensionalarray with N rows and N columns. You may assume a maximum size of 50 rows and 50 columns. 1. Write an algorithm MakeEmpty(n), which sets the first n rows and n columns to zero. 2. Write an algorithm Add(M1, M2, M3), which adds two matrices M1 and M2 together to produce matrix M3. 3. Write an algorithm Subtract(M1, M2, M3), which subtracts matrix M2 from matrix M1 to produce matrix M3. 4. Write an algorithm Copy(M1, M2), which copies matrix M1 into matrix M2.arrow_forward
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