Cross-Entropy - Explained
In this video, we talk about the cross-entropy loss function, a measure of difference between predicted and actual probability distributions that's widely used for training classification models due to its ability to effectively penalize prediction errors.
References
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Why We Don't Use the Mean Squared Error (MSE) Loss in Classification: • Why We Don't Use the Mean Squared Error (M...
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Contents
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00:00 - Intro
01:07 - Cross-Entropy Intuition
01:52 - Cross-Entropy in Information Theory
02:33 - Relationship with Softmax
03:43 - Outro
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