Based on the Gale-Shapley Algorithm, what would happen if we allow any man m or woman ww to have preference lists Pref( m), Pref(w) where |Pref(m)| < n or |Pref(w)| < n, n is the total number of men/women.
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- Write a python program based on the discussion we had on the last day of class, to train a network with two hidden layers each with 5 neurons. Finish the gradient computation we did in class, and implement a steepest decent search for a network which minimizes the cost function. Once you believe that your network is trained, compute the value of n(1, 1) and see what you get. Bonus: If you easily get this to work, then try to generalize to K neurons in each of the two hidden layers. Does the training work better with more neurons?Information is present in the screenshot and below. Based on that need help in solving the code for this problem in python. The time complexity has to be as less as possible (nlogn or n at best, no n^2). Apply divide-and-conquer algorithm in the problem. Make sure all test cases return expected outputs. Hint: Apply bisection method/modules Output FormatOutput contains a line with two space-separated integers W_a and W_b.- W_a is the maximum matchups won by Hamiltonia- W_b is the maximum matchups won by Burrgadia. Sample Input 03 554402410 Sample Output 03 0 Sample Input 15 4833485183 Sample Output 12 2 Sample Input 27 81028121912601319851 Sample Output 27 0 The actual code """Solves a test case Parameters:a : int - number of leaders in Hamiltoniab : int - number of leaders in Burrgadias_i : array-like - rap proficiencies of Hamiltonia's leadersr_j : array-like - rap proficiencies of Burrgadia's leaders Returns:win_a : int - number of…The language for coding must be in python Neural Network Units Implement a single sigmoid neural network unit with weights of [-1.2, -1.1, 3.3, -2.1] Calculate the outputs for two training examples:Example 1: [0.9, 10.0, 3.1, 1]Example 2: [0.9, 2.1, 3.7, 1] Note that you don't have to explicitly include a threshold or bias since the examples include a last element of 1 which means that the last weight effectively operates as a threshold. Assuming that a sigmoid unit response >0.5 denotes a positive class and <0.5 is negative class, is example 1 positive or negative? is example 2 positive or negative? Create a single ReLU unit and provide the outputs for those examples. Calculate the derivative of the sigmoid with respect to net input for both examples Calculate the derivative of the ReLU with respect to net input for both examples
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- Information is present in the screenshot and below. Based on that need help in solving the code for this problem in python. The time complexity has to be as less as possible (nlogn or n at best, no n^2). Apply greedy algorithm in the problem. Make sure both test cases return correct answers. Output Format The output consists of one line containing a single integer denoting the smallest possible maximum instability index among all the remaining universes. Sample Input 05 213134 Sample Output 05 Sample Input 16 4875876 Sample Output 125 Sample Input 28 713813331054 Sample Output 259 The actual code """This function solves a test case. Parameters:n : int - number of universesk : int - number of incursionsxs : array-like - list of instability indices Returns:An integer indicating the smallest maximum instability indices of the remaininguniverses"""def solve(n,k,xs): # TODO pass n,k = list(map(int,input().strip().split(" "))) xs = [int(input()) for i…Write a PYTHON program/script that will generate sequences of coin flips (with probability of heads p) and count the first flip when the full house condition (3 in a row) is met. Repeat this as many times as necessary to get a reasonable estimate of the probability that it takes k flips to get to a full house (k = 5, 6, 7 . . .). Plot these estimates vs k for p = 0.1 and p = 0.5.Information is present in the screenshot and below. Based on that need help in solving the code for this problem in python. The time complexity has to be as less as possible (nlogn or n at best, no n^2). Apply divide-and-conquer algorithm in the problem. Make sure all test cases return expected outputs by providing output screenshots. Provide screenshots Hint: Apply bisection method/modules Output FormatOutput contains a line with two space-separated integers W_a and W_b.- W_a is the maximum matchups won by Hamiltonia- W_b is the maximum matchups won by Burrgadia. Sample Input 03 554402410 Sample Output 03 0 Sample Input 15 4833485183 Sample Output 12 2 Sample Input 27 81028121912601319851 Sample Output 27 0 The actual code """Solves a test case Parameters:a : int - number of leaders in Hamiltoniab : int - number of leaders in Burrgadias_i : array-like - rap proficiencies of Hamiltonia's leadersr_j : array-like - rap proficiencies of…
- Information is present in the screenshot and below. Based on that need help in solving the code for this problem in python. The time complexity has to be as less as possible (nlogn or n at best, no n^2). Apply dynamic programming. Do not use recursion. Make sure ALL test cases return expected outputs. Output FormatOutput a single line containing the fastest time to get to square N from square 1. Sample Input 05 2 1 4 13 Sample Output 06 Explanation 0The optimal answer is to: RUN to square 2 (+2 seconds). Sonic now has 1 energy. DASH to square 3 (+1 second). Sonic now has 0 energy. RUN to square 4 (+2 seconds). Sonic now has 1 energy. DASH to square 5 (+1 second). Sonic now has 0 energy. Total time is 6 seconds. Sample Input 15 4 2 10 0 Sample Output 112 Explanation 1The optimal answer is to: RUN to square 2 (+4 seconds). Sonic now has 1 energy. RUN to square 3 (+4 seconds). Sonic now has 2 energy. DASH to square 4 (+2 seconds). Sonic now has 1 energy.…For the following netlist write a code in python for VLSI placement with simulated annealing M2 N006 Vinp N008 0 nfet1 l=1u w=4uM3 N007 Vinn N008 0 nfet1 l=1u w=4uM4 N003 N005 N006 0 nfet1 l=300n w=4uM5 N004 N005 N007 0 nfet1 l=300n w=4uM8 N002 N003 N004 VDD pfet1 l=300n w=8uM7 N001 N003 N003 VDD pfet1 l=300n w=8uM9 VDD N001 N001 VDD pfet1 l=1u w=8uM10 VDD N001 N002 VDD pfet1 l=1u w=8uM0 N008 Vbias 0 0 nfet1 l=2u w=16uM6 VDD N004 Vout VDD pfet1 l=0.5u w=32uM1 Vout Vbias 0 0 nfet1 l=2u w=128u .model nfet1 NMOS.model pfet1 PMOS *>> pairs M2 M3*>> pairs M4 M5*>> pairs M7 M8*>> pairs M9 M10 *>> port input Vinp*>> port input Vinn .backanno.end.Information is present in the screenshot and below. Based on that need help in solving the code for this problem in python. The time complexity has to be as less as possible (nlogn or n at best, no n^2). Apply dynamic programming. Include and use necessary libraries and packages. Make sure ALL test cases return expected outputs. Output FormatOutput a single line containing the fastest time to get to square N from square 1. Sample Input 05 2 1 4 13 Sample Output 06 Explanation 0The optimal answer is to: RUN to square 2 (+2 seconds). Sonic now has 1 energy. DASH to square 3 (+1 second). Sonic now has 0 energy. RUN to square 4 (+2 seconds). Sonic now has 1 energy. DASH to square 5 (+1 second). Sonic now has 0 energy. Total time is 6 seconds. Sample Input 15 4 2 10 0 Sample Output 112 Explanation 1The optimal answer is to: RUN to square 2 (+4 seconds). Sonic now has 1 energy. RUN to square 3 (+4 seconds). Sonic now has 2 energy. DASH to square 4 (+2…