This project dives into mathematical foundations of PAC learning theory while adding Python examples that make core ideas like generalization, sample complexity, VC dimension, halfspaces, perceptrons, and logical semantics executable and easier to inspect.
perceptron learning-theory generalization pac-learning vc-dimension sample-complexity ai-foundations theoretical-machine-learning probably-approximately-correct-learning pac-semantics
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Updated
Jun 24, 2026 - TeX