Question: What are the gradient (first derivative of the log-likelihood function) and the Hessian Matrix (second derivative of the log-likelihood function) when calculating the Maximum Likelihood

What are the gradient (first derivative of the log-likelihood function) and the Hessian Matrix (second derivative of the log-likelihood function) when calculating the Maximum Likelihood Estimators of parameters of a simple linear regression model with errors following a normal distribution with mean zero and constant variance?

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