If you use python please only use numpy and matplotlib

Fit the data {x(i),y(i)} for i=1,2,,n=8 using the model g(x)=0+1x+e2x Use gradient decent(GD) or stochastic gradient decent (SGD) to fit the data to the function g(x) by minimizing the RSS loss RSS()=i=1n(y(i)g(x(i)))2 Turn in any associated computations about gradients, your learning rate, the parameters and the RSS cost. (If you use both GD and SGD, one of them as bonus.)