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Lectures
Lecture 1: Classification metrics
Lecture 2: Regression metrics
Lecture 3: Feature engineering
Lecture 4: Feature importances and feature selection
Lecture 5: Loss functions, intro to regularization
Lecture 6: L2- and L1-Regularization
Lecture 7: Ensembles
Lecture 8: Model transparency and conclusion
Attribution
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