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01 ·Machine Learning Basics·★ MEMBER·10 min read Imbalanced Data in Practice — What to Optimize When 99% Is Normal When only 1% of your data is positive, accuracy lies. We build up from the confusion matrix to PR curves, class weighting, resampling, probability calibration, and deriving the decision threshold from cost — no prior knowledge assumed. 02 ·Machine Learning Basics·FREE·6 min read What Machine Learning Really Is — Understanding “Learning” Without the Math What actually separates writing a program from training a model. Rules versus examples, memorization versus generalization, and a map of supervised, unsupervised, and reinforcement learning — with almost no math.