+KL Divergence quantifies the information lost when one [Distribution](/wiki/distribution) is used to approximate another. It measures the "surprise" or difference between two probability models, playing a crucial role in [Information Theory](/wiki/information_theory) and guiding fields like [Machine Learning](/wiki/machine_learning) for model comparison and optimization.
+## See also
+- [Entropy](/wiki/entropy)
+- [Information Theory](/wiki/information_theory)
+- [Machine Learning](/wiki/machine_learning)
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