Stop 06 · Feature Engineering & Model EvaluationTopics · 2/12
One-Hot & Label Encoding
Part of the AI Engineer Roadmap
In short
Turning categorical variables into numeric form models can consume — one-hot for unordered categories, label/ordinal encoding for ordered ones.
How to learn this
- 1Practice both encoding types with pandas `get_dummies` and scikit-learn encoders.
- 2Learn when one-hot encoding blows up dimensionality and what to do about it.
- 3Understand target/mean encoding as an alternative for high-cardinality categoricals.
More topics at this stop
Feature Scaling & NormalizationFeature SelectionHandling Imbalanced DataHyperparameter Tuning (Grid/Random Search)Ensemble Methods (Bagging, Boosting)XGBoost & LightGBMEvaluation Metrics (Accuracy, Precision, Recall, F1)ROC-AUCConfusion MatrixBias-Variance TradeoffOverfitting & Regularization (L1/L2)
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