Q / write Matlab code that asks the user to enter several (elements (N) in Vector (V) -: uses (input )then ask the user to enter the values of elements of the vector: use (inputting)

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()

Answer in C++ code please! (Duplicate Elimination with vector) Use a vector to solve the following problem. Read in 20 numbers, each of which is between 10 and 100, inclusive. As each number is read, validate it and store it in the vector only if it isn't a duplicate of a number already read. After reading all the values, display only the unique values that the user entered. Begin with an empty vector and use its push_back function to add each unique value to the vector.

Complete the following function that counts the even numbers in a 2D vector of integers. int count_evens(const std::vector<std::vector<int>>& v) { // Add your code... } Please add output screenshot!

Complete the C++ code below#include "std_lib_facilities.h"/*1. Define a function which calculates the outer product of two vectors. The function return is a matrix. */vector<vector<int>> outerProduct(vector<int>& A, vector<int>& B){//implement here}/*2. Define a function which transposes a matrix. */vector<vector<int>> transpose(vector<vector<int>>& A){//implementation}/*3. Define a function which calculates the multiplication of a matrix and it's transpose. */vector<vector<int>> product(vector<vector<int>>& A){// implementation}/*4. Define a print out function that will print out a matrix in the following format:Example: a 3 by 4 matrix should have the print out:1 2 3 42 3 4 53 4 5 6*/void printMatrix(vector<vector<int>>& A){// implementation}int main(){// Define both vector A and vector Bvector<int> A = {1 ,2, 3, 4, 5};vector<int> B = {1, 2, 3};/*Test outerProduct…

Use iterators to print each element of v separted by spaces. #include <iostream>#include <vector> using namespace std; int main(){vector<int> v = {1, 3, 5}; (.....) }

Write the following function #input: a numerical vector x #output:the normalized vector, i.e. the vector rescaled into [0,1] # the formula to normalize is (x-min(x))/ (max(x)-min(x)) # you can NOT use the functions min and max # you can use %%, nrow, ncol, and length # you can write multiple functions

You may insert an element into an arbitrary position inside a vector using an iterator. Write a function, insert(vector, value) which inserts value into its sorted position inside the vector. The function returns the vector after it is modified. #include <vector>using namespace std; vector<int>& insert(vector<int>& v, int value){ ................ return v; }

3. Use two vectors and make them into one. Use the following vectors:Vector#1 {1, 1, 5, -3, 0}Vector#2 {9,7,2}Return a vector containing 1, 1, 5, -3, 0, 9, 7, 2 (in that order)

import numpy as np import torch import matplotlib.pyplot as plt Quiz Preparation Question 1. Write a function that generates a random tensor of n x n (n is the input). The output is the mean of the tensor. = 2, 4, 8, 16, ... 1024 and generate a vector 2. Write a code (for loop) that call that calls the function above with n = M(n). Plot the vector as a function of the log of n. 3. Given an n x m array write a code that replaces every element that is larger than 0.5 with 0.5. 4. The second derivative of a function can be approximated by the finite difference 1 ƒ"(x₂) = 73 (ƒ(£;+1) — 2ƒ(x;) + f(x;-1)) Given a vector f with values f = [f(xo),..., f(n) write a code that computes the approximation to f"(x) 5. The power method is a method to compute the largest eigenvalue of a matrix. Your google search is using this method every time you perform a google search. The method consists of the iteration Vj+1 = Av; || Avi|| where v; is a vector with chosen as a random vector, and A is the matrix…