Overfitting

All That Glitters Is Not Gold: Comparing Backtest and Out-of-Sample Performance on a Large Cohort of Trading Algorithms

Machine Learning's First Cheating Scandal

A post-mortem on a Kaggle-era incident where participants gamed the public leaderboard through repeated test-set probing — effectively overfitting to held-out data via the submission API. Raised serious questions about how ML benchmarks and competitions should be designed.

Overfitting, Regularization, and Hyperparameters

DS Walter's practitioner explainer on overfitting, regularization techniques, and hyperparameter tuning — covering L1/L2 penalties, dropout, and cross-validation. A clear introduction to the bias-variance tradeoff for working data scientists.