**References**

**Notes** {{word-count}}

**Summary**:

**Key points**:

$\theta^{\star} \leftarrow \arg \min _{\theta}-\sum_{i} \log p_{\theta}\left(y_{i} \mid x_{i}\right)$

The $-\sum_{i} \log p_{\theta}\left(y_{i} \mid x_{i}\right)$ part is also a Loss Function.

This is also called Cross-Entropy.

Negative Log-Likelihood (NLL) is sometimes also called as Cross-Entropy.

This is called the Maximum Likelihood Estimation (MLE), and it can be formulated as a Negative Log-Likelihood (NLL) problem.