10.5) Softmax and Cross Entropy

Описание к видео 10.5) Softmax and Cross Entropy

Chapter 10:

Softmax and Cross-Entropy are key components in multi-class classification tasks. Softmax is an activation function that converts the model's raw outputs (logits) into probabilities across all classes, ensuring they sum to 1. Cross-Entropy is the loss function used to measure the difference between the predicted probabilities from softmax and the actual labels, guiding the model to minimize error.

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