unction loss = loss_func(t_hat, t) that computes the empirical loss in matlab

Here is one implementation of the loss_func function in MATLAB that computes the empirical loss given the predicted target values t_hat and the true target values t:

main.m
function loss = loss_func(t_hat, t)
% Computes the empirical loss given the predicted target values t_hat
% and the true target values t.
% Inputs:
%   - t_hat: a vector of predicted target values
%   - t: a vector of true target values
% Output:
%   - loss: the empirical loss

% Compute the element-wise squared error between predicted and true values
error = (t_hat - t).^2;

% Compute the average loss over all samples
loss = mean(error);
end
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In the above implementation, we first compute the element-wise squared error between the predicted and true target values using the error variable. Next, we compute the mean of error to obtain the empirical loss, which is returned by the function.

This implementation uses vectorized computation, which can be more efficient than computing the loss in a loop over individual samples.