The choice of loss function defines what your model optimizes. MSE, cross-entropy, hinge loss, and contrastive losses each encode different assumptions.
Learning Objectives
→Derive binary cross-entropy from MLE
→Implement categorical cross-entropy
→Understand triplet and contrastive losses
→Choose loss function given task type
Practice
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