. c) Implement gradient descent algorithm to minimize the cost function. • Assign initial values of W=(wo, W1, W2) to ze

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C Implement Gradient Descent Algorithm To Minimize The Cost Function Assign Initial Values Of W Wo W1 W2 To Ze 1 (42.87 KiB) Viewed 32 times

Note: Please, write your codes in Python.
. c) Implement gradient descent algorithm to minimize the cost function. • Assign initial values of W=(wo, W1, W2) to zero or choose randomly • Learning rate: alpha=0.001, you can change it in different experiments • Number of iterations: 10000 or you can stop it when two sequential values are too close. • Calculate values of parameters using gradient descent formula. wy:= w;-a- C-º) (h(x) - y)^2 n i=1