69. Feature Engineering: Building Better Inputs

You've tried three different algorithms. None of them break 78% accuracy. You add dropout, tune hyperparameters, try XGBoost. Still stuck. Then you create one new feature from the existing data. Accuracy jumps to 86%. That's feature engineering. And it's the part of ML that makes the biggest difference in practice. Not the algorithm. Not the hyperparameters. The features. This post covers the core techniques you'll actually use on real datasets. What You'll Learn Here Why features matter more th