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#overfitting

2 articles

01 ·Probability & Statistics·★ MEMBER·PAPER·11 min read Statistical Learning Theory — Why Does Learning Generalize? You only ever see finitely many examples, yet the model answers questions about data it has never seen. This piece builds the guarantee from scratch — Hoeffding, uniform convergence, VC dimension, PAC — then shows where it broke against deep learning, and what survives in day-to-day evaluation design. 02 ·Machine Learning Basics·★ MEMBER·8 min read Overfitting and Evaluation Design — Be Suspicious of 99% Accuracy Why a model that fits its training data perfectly falls apart in production: the division of labour between train, validation and test, cross-validation, the data leakage that ruins more projects than any modelling mistake, and how accuracy lies on imbalanced data.