Research First: Beating Kaggle's Titanic with History Books
Most Kaggle Titanic tutorials open with
import pandas as pdand immediately start running.describe(). I did something different: I read about the actual disaster first.The result was better feature engineering, more informed imputation strategies, and a clearer picture of what was noise versus signal. The model barely mattered — the features did all the work.
Why Research Before Code
The Titanic dataset has 891 rows and 11 features. You could get ~77% accuracy by predicting “all women survive, all men die.” Getting past 77% requires understanding why people survived beyond gender. That understanding comes from the history, not the data.