How is a loss function equal to the negative log likelihood function of the outcome distribution

boosting

#1

Hello,

In the above image the highlighted part says something which I didn’t quite understand.
1.Is f the linear regression equation mapping x and y?
2.The p is the residuals as a function of x’s?
3.How is p equivalent to the negative log-likelihood of the gaussian model??