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Common loss functions, like the cross-entropy or mean squared error, are chosen because, if you minimize them, you are actually maximizing the likelihood of the parameters given the observed data. In other words, you are trying to find the probability distribution $p(y \mid x; \theta)$, parametrized by $\theta$ (the parameters of your model), which is most ...

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