A Visual Introduction to Machine Learning
Summary
R2D3 provides a visual, beginner-friendly tour of core machine learning ideas using a San Francisco vs New York housing example. It covers features, decision trees, training versus test data, overfitting, and how splits and leaf nodes drive predictions, framed as accessible intuition rather than code. The piece notes tradeoffs like false positives/negatives and introduces related concepts in footnotes.