Published on: 2025-04-30 16:48:48
April 12, 2025 at 06:54 Tags Math , Machine Learning Cross-entropy is widely used in modern ML to compute the loss for classification tasks. This post is a brief overview of the math behind it and a related concept called Kullback-Leibler (KL) divergence. Information content of a single random event We'll start with a single event (E) that has probability p. The information content (or "degree of surprise") of this event occurring is defined as: \[I(E) = \log_2 \left (\frac{1}{p} \right )\] Th
Keywords: cross entropy kl log_2 probability
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